Evaluation Methods for the Cooperative Tracking Performance of High- and Low-Earth Telescopes on GEO Targets

Abstract

This invention provides a method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets. The method includes: sampling data of basic indicators at the bottom level; for each basic indicator, first mapping its data to a set of evaluation levels, and then statistically obtaining a membership vector; aggregating from the bottom-level indicators until obtaining the membership vector of the top-level basic indicators; determining the score of the telescope combination scheme; and evaluating the scheme's performance based on the score. The basic indicators include full-load observation performance, observation performance, utilization rate, relay capability, orbit determination capability, guidance capability, relay success rate, orbit determination accuracy, orbit determination arc length, deviation, and response interval at different levels. This invention's method is based on D-S evidence theory for sampling, membership calculation, indicator aggregation, and evaluation, establishing a comprehensive performance evaluation index system. It can utilize performance weights to rank the merits of telescope combination schemes according to specific task requirements.

Description

Technical Field

[0001] This invention belongs to the field of astronomical telescopes, specifically relating to an evaluation method for the collaborative tracking performance of high-low pairing telescopes on GEO targets. Background Technology

[0002] In response to the frequent maneuvering behavior of geosynchronous orbit (GEO) targets and the need for comprehensive space situation awareness, the observation network usually urgently calls upon a combination of high- and low-precision telescopes to conduct joint observations after the survey telescopes detect space target maneuvers or discover unknown targets, in order to obtain data with higher observation accuracy, as well as clearer observation images or other feature information.

[0003] Currently, common high-low combination telescope collaborative tracking and guidance methods include positioning point calculation guidance method, sparse arc segment orbit determination guidance method, and multi-station equipment synchronous measurement guidance method.

[0004] High-low mix telescopes typically operate on their main observation network. Currently, my country lacks a systematic evaluation method for high-low mix telescopes. For example, there is no specific evaluation method for the aforementioned collaborative tracking and guidance method for high-low mix telescopes. Existing evaluations focus on other aspects, such as the performance evaluation of individual telescopes, the evaluation of GEO recognition capabilities in a large field of view, and the evaluation of the observational effectiveness of space-based observation orbits. These methods cannot directly evaluate the observational effectiveness of multiple telescope combinations. If simulation evaluations are conducted using these methods, firstly, the data utilization rate is extremely low, and secondly, the evaluation results are not comprehensive enough. Summary of the Invention

[0005] The purpose of this invention is to provide a method for evaluating the collaborative tracking performance of high-low combination telescopes on GEO targets, so as to achieve a comprehensive evaluation of telescope combination schemes.

[0006] To achieve the above objectives, the present invention provides a method for evaluating the cooperative tracking performance of high-low combination telescopes for GEO targets, comprising:

[0007] S1: Data of the underlying basic indicators are sampled during the operation of the telescope combination scheme;

[0008] S2: For each underlying indicator in the basic indicators, firstly map each data of the underlying indicator to the set of evaluation levels, then count the set of evaluation levels to which all data of the underlying indicator belong to obtain the basic assignment function of each set of evaluation levels as the membership degree, and combine them to obtain the membership degree vector of the underlying indicator.

[0009] S3: Based on the DS evidence theory, starting from the bottom-level indicators, the basic indicators of the lower level are aggregated to obtain the membership vector of the basic indicators of the upper level, until the membership vector of the top-level basic indicators is obtained.

[0010] S4: Determine the score of the telescope combination scheme based on the membership vector R and performance weight of the top-level basic indicators obtained in step S3; evaluate the performance of different telescope combination schemes based on their scores, with higher scores indicating better performance; the basic indicators include the full-load observation performance at the top level, the observation performance and utilization rate at the lower level of full-load observation performance, the relay capability and orbit determination capability at the lower level of observation performance, the guidance capability and relay success rate at the lower level of relay capability, the orbit determination accuracy and orbit determination arc length at the lower level of orbit determination capability, and the deviation and response interval at the lower level of guidance capability.

[0011] In step S1, the formula for calculating the deviation is: P is the decomposition matrix of the two-dimensional covariance of the location distribution represented by the guiding data. is the distance vector from the target observed by the guided telescope to the center of the guiding position;

[0012] The formula for calculating the response interval is: t 2，i，Y，T -max X [t 1，i，X |T},

[0013] Among them, t 1,i,X t is the time when the X-guided telescope receives the observation data returned by its measuring equipment during the i-th phase of the mission. 2,i,Y,T The moment when the controller of guided telescope Y issues an observation request to target T during the i-th phase of the mission, where i is the mission phase number, X is the ordinal number of the guiding telescope, Y is the ordinal number of the guided telescope, T is the ordinal number of the target, and max X {t 1,i,X |T} is the last moment when all the guiding telescopes receive the observation data containing target T returned by their measuring instruments during the i-th phase of the mission;

[0014] The formula for calculating the success rate of a relay race is:

[0015]

[0016] Among them, Quest number Quest represents the total number of times all relay missions have been issued. victory The number of successful relay missions;

[0017] Orbit determination accuracy refers to the precision of the orbit determination result obtained from all observation data from a single target of the guided telescope;

[0018] The formula for calculating the fixed-track arc length is: max Y {t 3，i，Y，T}-mini，X {t 1，i，X，T},

[0019] In the formula, t 3,i,Y,T The max value represents the moment when the central control receives observation data or failure information about target T sent back by the guided telescope Y during the i-th phase of the mission. Y {t 3,i,Y,T} is the last moment in phase i of the mission when all guided telescopes send back observation data or failure information about target T. 1,i,X,T It is the moment, min, when the X-guide telescope receives the observational data containing target T returned by its measuring equipment during mission phase i. i,X {t 1,i,X,T} is the earliest moment when all guiding telescopes receive observational data containing target T returned by their measuring equipment at all mission phases.

[0020] The formula for calculating utilization rate is:

[0021] Where N is the total number of guided telescopes in the scheme, and time j The operating time of the j-th guided telescope is time. all This represents the total duration of this observation.

[0022] In step S2, mapping each data point of the underlying indicators to the set of evaluation levels means mapping the data of the underlying indicators to the elements of the power set of evaluation levels {{good}, {good, medium}, {medium}, {medium, poor}, {poor}, {good, medium, poor}}, where each element of the power set represents a set of evaluation levels. All underlying indicators are divided into quantitative and qualitative indicators. The method for mapping quantitative indicators to the set of evaluation levels is to use an evaluation function to rate different data points of the underlying indicators. The method for mapping qualitative indicators to the set of evaluation levels is to first perform quantile normalization on the different data points of the underlying indicators and then use an evaluation function to rate them. And / or in step S3, the specific form of the membership vector R of the top-level basic indicators is:

[0023]

[0024] Where m({A}), m({A,B}), m({B}), m({B,C}), m({C}), and m({A,B,C}) are the basic allocation functions of the sets {A}, {A,B}, {B}, {B,C}, {C}, and {A,B,C} corresponding to the top-level basic indicators, respectively. A, B, and C represent good, average, and poor, respectively.

[0025] The quantitative indicators include deviation and orbit determination accuracy, while the qualitative indicators include response interval, relay success rate, orbit determination arc length, and utilization rate.

[0026] The guiding telescope is a general survey telescope, and the guided telescope is a precision survey telescope.

[0027] Step S3 specifically includes:

[0028] S31: The aggregation formula is modified using the weighting coefficients of the lower-level indicators to obtain the aggregation formula for the upper-level basic indicators; after modification, the aggregation formula for the upper-level basic indicators is:

[0029]

[0030] Where m is the basic allocation function of the upper-level basic indicators, m(A) represents the probability that the upper-level basic indicators belong to the set A of evaluation levels, i = 1 to n, n is the number of lower-level basic indicators, and A represents the set to which the upper-level basic indicators belong. i It is the basic allocation function of the lower-level basic indicators, A i ω represents the set to which the lower-level basic indicators belong. i It is the weighting coefficient of the lower-level indicators;

[0031] S32: Using the aggregation formula in step S31, starting from the lowest level of basic indicators, aggregate the basic indicators of the lower level to obtain the membership vector of the basic indicators of the upper level, until the membership vector of the top level basic indicators is obtained.

[0032] The weighting coefficients for the lower-level indicators include:

[0033]

[0034] Where W is the weight allocation coefficient of the lower-level indicators of full-load observation efficiency, and W1 is the weight allocation coefficient of the lower-level indicators of observation efficiency. 1.1 W is the weighting coefficient for the lower-level indicators of relay capability. 1.2 W is the weighting coefficient for the lower-level indicators of orbit determination capability. 1.1.1 Weighting coefficients for lower-level indicators of guiding capability; and / or

[0035] The performance weights corresponding to the membership vectors of the top-level basic indicators are preset or adjusted by the user according to task requirements.

[0036] Step S4 further includes: after evaluating the effectiveness of different telescope combination schemes, performing the following operations based on the evaluation results: guiding the site selection of newly built guiding or guided telescopes based on the scores; selecting the telescope combination scheme with the best performance based on the scores.

[0037] Step S32 further includes: in each process of aggregating the lower-level basic indicators to obtain the upper-level basic indicators, multiplying and summing the membership degrees of the lower-level basic indicators to obtain the sum of the unnormalized membership degrees of the upper-level basic indicators as the evidence consistency degree of the upper-level basic indicators; Step S4 further includes: judging whether there are significant defects in the upper-level basic indicators of each telescope combination scheme based on the evidence consistency degree of each upper-level basic indicator; and guiding the improvement of the site facilities of the guiding or guided telescopes based on the evidence consistency degree.

[0038] Step S4 further includes: calculating and determining the similarity of different telescope combination schemes based on the membership vector of the top-level basic indicators of different telescope combination schemes, and determining whether the weight allocation coefficients of the lower-level indicators need to be adjusted based on the task completion degree of different telescope combination schemes in the actual task.

[0039] This invention, based on the workflow of high-low pairing telescopes collaborative tracking, proposes weighted indicators at different levels, such as deviation, relay success rate, telescope utilization rate, and feature enhancement degree. Based on DS evidence theory, it establishes a comprehensive performance evaluation indicator system through data sampling, membership calculation, indicator aggregation, and result evaluation. This system covers aerospace measurement, orbit determination, and situational awareness. Furthermore, performance weights can be used to rank the effectiveness of telescope combination schemes according to specific mission requirements. By continuously monitoring high-low pairing telescope collaborative tracking missions, quantitative and normalized performance evaluation values ​​can be obtained, providing suggestions for improving the operation and management of the observation network, solving the problems of collaborative tracking resource allocation and observation plan optimization, and achieving efficient operation of the observation network. Compared with traditional observation network performance evaluation methods, this invention has the ability to comprehensively evaluate observation performance from multiple levels and dimensions, and the evaluation indicators are not fixed and can be expanded. Attached Figure Description

[0040] Figure 1 This is a timing diagram of the evaluation object in the operation of the evaluation method for the cooperative tracking performance of high and low paired telescopes of the present invention.

[0041] Figure 2 This is a hierarchical structure diagram of the basic indicators of the collaborative tracking performance of high and low paired telescopes for GEO targets in this invention.

[0042] Figure 3 This is a flowchart of the index aggregation of the collaborative tracking performance of high and low paired telescopes for GEO targets according to the present invention.

[0043] Figure 4 This is a hierarchical extended structure diagram of the basic indicators of the collaborative tracking performance of the high and low paired telescopes of the present invention for GEO targets. Detailed Implementation

[0044] The evaluation method for the collaborative tracking performance of high-low combination telescopes in this invention is used to comprehensively evaluate telescope combination schemes corresponding to high-low combination telescopes. It must meet the quantitative or qualitative requirements of several indicators, while also favoring certain indicators based on actual conditions. To meet the quantitative or qualitative requirements, the evaluation method of this invention provides evaluation rules for the specific values ​​of the underlying indicators. To meet different mission requirements, the evaluation method of this invention stratifies and assigns weights to different indicators.

[0045] Figure 1 This is a timing diagram of the evaluation object in operation of the evaluation method for the cooperative tracking performance of high-low combination telescopes of the present invention, wherein the evaluation object is the telescope combination scheme corresponding to the high-low combination telescopes.

[0046] like Figure 1 As shown, the operation process of the telescope combination scheme corresponding to the high and low combination of telescopes is as follows:

[0047] Step A1: The central control sends a relay mission to the controller at the station of the X-guided telescope at regular intervals;

[0048] Typically, the guiding telescope is a general survey telescope, while the guided telescope is a precision survey telescope.

[0049] In the i-th phase of the task, the central authority issues the relay task T. X,i The time is t 0,i Each time the central command issues a new batch of relay tasks, it is considered a new phase.

[0050] It should be noted that the overall mission includes the monitoring of many targets. During observation, some targets may have moved and become undetectable. The observed targets may not be limited to the targets in the mission. These additional targets are unidentified targets, which may be newly discovered or may be targets that have moved after the original targets.

[0051] Step A2: The X-guided telescope station, according to the relay mission, periodically sends the observation request Q. X,i The controller sends data to its measuring equipment to perform observations, enabling the controller to receive the observation data D returned by the measuring equipment. X,i And send it to the central hub;

[0052] The time at which the X-guide telescope receives the observation data returned by its measuring equipment during the i-th phase of the mission is t. 1,i,X i is the mission phase ordinal number, X is the ordinal number of the guiding telescope, and T is the ordinal number of the target.

[0053] Step A3: The central nervous system utilizes existing observation data D X,iEstimate the trajectories of all unidentified targets to generate guiding data L. Y,i The site assigned to the Y-guided telescope;

[0054] In the i-th phase of the mission, the time when the controller of the Y-guided telescope sends an observation request to the T-target is t. 2,i,Y,T i is the mission phase ordinal number, Y is the ordinal number of the guided telescope, and T is the ordinal number of the target.

[0055] The data returned by the guiding telescope is the observation's corresponding [time, right ascension, declination], but it does not identify the target. Target identification is handled by the central system. Because the field of view of general observations is large and may overlap, the central system, like a person with two eyes, makes more accurate judgments. The guided telescope only processes or prioritizes processing unidentified targets, because successfully identified targets have a large amount of historical observation data in the database that can be used for orbit determination, while unidentified targets require high-quality data to achieve accurate and rapid orbit determination.

[0056] Step A4: The site of the guided telescope Y will send the observation request Q. Y,i,T The controller sends data to its measuring equipment to perform observations, enabling the controller to receive the observation data D returned by the measuring equipment. Y,i,T And will realize the observation data D during the relay Y,i,T Failure information F when relay is not completed Y,i,T Send to the central hub.

[0057] Observational data D Y,i,T It is usually precise measurement data.

[0058] Among them, the central system received observation data D of target T sent back by the Y-guided telescope during the i-th phase of the mission. Y,i,T Or failure message F Y,i,T The moment is t 3,i,Y,T .

[0059] The complete process from steps A1 to A4 is called a stage, meaning that the central hub issues a batch of relay tasks T each time. X,i This corresponds to a phase. The phase of a task is a concept weakly related to time. The central hub issues a relay task, guiding the telescopes to perform observations and periodically return data to the central hub. The central hub will use the existing data to estimate the trajectories of all unidentified targets and generate guidance data to be distributed to the guided telescopes. After the guided telescopes observe, they return the data to the central hub. This complete process is called a phase.

[0060] It should be noted that the timeframes for each stage may overlap for the entire system. For example, the detailed observations in the first stage (step A4) may not be completed while the general observations in the second stage (step A2) are already underway. It is clear that each type of telescope (guided or guided) (potentially multiple telescopes) can only be in a specific stage at a time. That is, a guiding telescope can only be in a unified first stage at any given time, and a guided telescope can only be in a unified second stage at any given time. The first stage may or may not be equal to the second stage.

[0061] The satellites observed in each phase may differ. Specifically, when the guiding telescope observes a new unidentified target, the central system guides the guided telescope to achieve rapid orbit determination, thus increasing the number of targets. If an unidentified target achieves sufficient orbit determination accuracy based on the feedback data from the previous phase, the guiding telescope will no longer consider it a target for observation in the next phase, thus reducing the number of targets.

[0062] exist Figure 1 In the middle, all the marked data (i.e., t) 0,i t 1,i,X t 2,i,Y,T t 3,i,Y,T All of these need to be collected, as the calculation of the underlying indicators in the evaluation method of this invention requires the use of this data.

[0063] X and Y are the station numbers of the guiding telescope and the guided telescope, respectively. In a telescope combination scheme, there may be one or more values ​​for X or Y. For example, in a telescope combination scheme of two general survey telescopes (numbered 1001 and 1005) and one precision survey telescope (numbered 1009), X corresponds to 1001 and 1005. Since the precision survey telescope is guided by the general survey telescope by default, in this embodiment, the station number X of the guiding telescope corresponds to the general survey telescope, and the station number Y of the guided telescope corresponds to the precision survey telescope.

[0064] In other embodiments, provided that future technological developments allow, it should also be permissible for a general survey telescope to guide another general survey telescope. Therefore, the design distinguishes X and Y to represent the station numbers of the guiding telescope and the guided telescope, respectively, so that it can be applied without explicitly distinguishing between general survey telescopes and precision survey telescopes.

[0065] Regarding the aforementioned telescope combination schemes, this invention provides a method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets. This method is based on the DS evidence theory and includes:

[0066] Step S1: During the operation of the telescope combination scheme, sample and obtain the underlying basic index data;

[0067] In this embodiment, the basic indicators include: full-load observation efficiency, observation efficiency, utilization rate, relay capability, orbit determination capability, guidance capability, relay success rate, orbit determination accuracy, orbit determination arc length, deviation, and response interval.

[0068] like Figure 2 As shown, the basic indicators include the full-load observation efficiency at the top level, the observation efficiency and utilization rate at the lower level of full-load observation efficiency, the relay capability and orbit determination capability at the lower level of observation efficiency, the guidance capability and relay success rate at the lower level of relay capability, the orbit determination accuracy and orbit determination arc length at the lower level of orbit determination capability, and the deviation and response interval at the lower level of guidance capability.

[0069] Therefore, the underlying indicators include deviation, response interval, relay success rate, orbit determination accuracy, orbit determination arc length, and utilization rate, all of which are derived from experimentally collected data. Step S2 will describe the normalization method for the underlying indicator data. The remaining indicators will be obtained from their subordinate indicators through the aggregation method of DS evidence theory, which will be detailed in step S3.

[0070] The following details the process of obtaining data for each basic indicator.

[0071] Deviation: Deviation is used to measure the accuracy of the guidance data provided by the guidance telescope.

[0072] In this embodiment, the deviation is neither the precision of the guidance data nor the distance from the target to the guidance center. Let Σ be the two-dimensional covariance of the position distribution represented by the guidance data, and let Σ be the distance vector from the target observed by the guided telescope to the guidance position center. Since the two-dimensional covariance Σ of the location distribution represented by the guiding data is a positive definite matrix, there exists a decomposition matrix P that satisfies the formula P T P = Σ -1 Specifically, the formula for calculating the deviation is as follows: P is the decomposition matrix of the two-dimensional covariance of the location distribution represented by the guiding data. is the distance vector from the target observed by the guided telescope to the center of the guiding position.

[0073] During the operation of the telescope combination scheme, the central processing unit processes the acquired observation data to obtain orbital data, and further processes it to obtain guidance data. The difference between guidance data and orbital data is as follows: Orbital data is a normal distribution in 3D space at each moment. Guidance data is obtained by transforming the orbital data to the celestial coordinates of a site of the guided telescope, integrating it along the distance direction to form a normal distribution in 2D space along the right ascension and declination of that site. The positional distribution represented by guidance data over a 3σ range may require multiple fields of view from the guided telescope to cover. The observation data from the guided telescope is in the form of direct observational data images and the time, right ascension, and declination corresponding to the synchronous target in the field of view. Deviation measures the ability of the guidance data to enable precise observation of the target, so it is two-dimensional data in space.

[0074] Response interval: The response interval measures the validity period of boot data. The larger the response interval, the greater the possibility of boot failure; therefore, boot data has an expiration period.

[0075] In this embodiment, the response interval is the time interval between the controller of the guiding telescope receiving the observation data and the measurement device of the guided telescope receiving the observation request. The response interval is affected by factors such as the time for generating guiding data, the time for transmitting data, the time for reading data, the task queuing situation, and the weather conditions. Specifically, it is affected by the amount of data returned by the guiding telescope, the guiding data calculation method used by the central system, and the task execution queuing situation of the guided telescope.

[0076] Therefore, the formula for calculating the response interval is t. 2，i，Y，T -max X {t 1，i，X |T}.

[0077] Among them, t 1,i,X t is the time when the X-guided telescope receives the observation data returned by its measuring equipment during the i-th phase of the mission. 2,i,Y,T The moment when the controller of guided telescope Y issues an observation request to target T during the i-th phase of the mission, where i is the mission phase number, X is the ordinal number of the guiding telescope, Y is the ordinal number of the guided telescope, T is the ordinal number of the target, and max X {t 1,i,X |T} is the last moment at which all guiding telescopes receive observational data containing target T, returned by their measuring instruments during mission phase i.

[0078] Therefore, the response interval is the time interval between the completion of the collection of observational data used to generate the guidance data at the front end and the start of guidance by the guided telescope for each target. Any target may generate this indicator at any stage of the mission, and multiple response intervals can be generated in a relay mission for a single target (i.e., a relay mission), and they are generated in pairs with the deviation.

[0079] The factors influencing the number of response intervals generated in a relay mission targeting a single target are as follows: If a target successfully completes a relay on the first attempt, it generates only one response interval; if a target fails once before successfully completing a relay, the failed attempt is also recorded. This can be analogized to target shooting: hitting the target ends the mission, and the shooting distance (response interval) and the score (miss or deviation) for each shot are recorded. There are cases where a target can be successfully relayed multiple times. If the orbit determination result for a target is poor, more guiding and / or guided telescopes will participate in its orbit determination, resulting in multiple relays for that target.

[0080] Guiding capability: Guiding capability is a higher-level indicator than deviation and response interval, used to evaluate the guiding capability of a guiding telescope.

[0081] For a specific relay of a target, the longer the response interval, the greater the deviation. Therefore, the response interval and deviation can form a monotonically decreasing function, and we can only collect one point from this function of response interval and deviation each time. To compare relays from different sources (relays from different targets or relays from different batches of the same target), similar to comparing different functions, and the guidance capability is equivalent to the magnitude of the decisive parameter in this function, this invention uses DS aggregation theory and corresponding index aggregation process to achieve a function similar to comparing the decisive parameter (i.e., guidance capability) corresponding to different functions of response interval and deviation, thus obtaining the numerical value of guidance capability.

[0082] Relay success rate: The relay success rate is used to reflect the relay capability of a telescope combination scheme.

[0083] During a single observation by the guiding telescope, there may be multiple unidentified targets, which will result in multiple tasks being assigned to the guided telescope.

[0084] In this case, the formula for calculating the relay success rate is:

[0085]

[0086] Among them, Quest number Quest represents the total number of times all relay missions have been issued. victory This represents the number of successful relay missions.

[0087] In other words, Quest number It's not the total number of relay tasks (because relay tasks sometimes fail), but rather that each relay task initiation is considered a Quest.

[0088] Relay capability: Relay capability is a higher-level indicator than guidance capability and relay success rate, used to evaluate the system's relay ability. Compared to guidance capability, this indicator adds factors related to the interaction between the guiding telescope and the guided telescope within the system, for the following two considerations:

[0089] 1) When the standard deviation of the guiding data is too small, a larger deviation can still meet the relay requirements; 2) When the long response interval required by the system is a common phenomenon in this scheme, there should be higher requirements for the validity period of the guiding data.

[0090] Similar to the above, the relay capability value is obtained through the DS aggregation theory and corresponding indicator aggregation process, which will be detailed below. All non-bottom-level indicators are obtained by aggregating lower-level indicators.

[0091] Orbit determination accuracy: Orbit determination accuracy refers to the accuracy of the orbit determination result obtained from all observation data from a single target of the guided telescope.

[0092] The accuracy of orbit determination is related to the orbit determination method. The orbit determination algorithm proposed in this invention is the sequential orbit determination method, but other orbit determination methods can also be used. In this invention, there is no fixed formula for orbit determination accuracy; only the data used to calculate the orbit determination accuracy is specified.

[0093] All observational data here refers to all observational data of this target within the central control area after each guided telescope returns. As the mission progresses, the amount of observational data for this target will increase.

[0094] Orbit determination arc length: Orbit determination arc length represents the time span of all observation data used for orbit determination of a single target.

[0095] The formula for calculating the fixed-track arc length is:

[0096] max Y {t 3，i，Y，T}-min i，X {t 1，i，X，T},

[0097] In the formula, t 3,i,Y,T The max value represents the moment when the central control receives observation data or failure information about target T sent back by the guided telescope Y during the i-th phase of the mission. Y {t 3,i,Y,T} is the last moment in phase i of the mission when all guided telescopes send back observation data or failure information about target T. 1,i,X,T It is the moment, min, when the X-guide telescope receives the observational data containing target T returned by its measuring equipment during mission phase i. i,X {t 1,i,X,T} represents the earliest moment when all guiding telescopes receive observational data containing target T returned by their measuring equipment across all mission phases, corresponding to the earliest moment when the central telescope receives data containing that target. Note the presence of 'i' in the subscript of 'min', which means that all currently existing phases have been traversed.

[0098] Since the orbit determination data is in the format of [station coordinates + time + right ascension and declination], min i,X {t 1,i,X,T The method for obtaining} is to take the minimum value of the time in the orbit determination data corresponding to all the observation data of the target obtained in the relay mission corresponding to this target.

[0099] Any target may generate orbital arc lengths at any stage of the mission, and multiple orbital arc lengths can be generated in a mission corresponding to a target, and they are generated in pairs with the orbital accuracy.

[0100] Track determination capability: Track determination capability is a higher-level indicator than track determination accuracy and track determination arc length, and is used to evaluate the track determination capability of a scheme.

[0101] Utilization: Utilization measures the time and resource consumption of a telescope combination scheme. All other things being equal, a lower utilization rate indicates that the system is more likely to perform better in high-intensity tasks.

[0102] In this embodiment, the formula for calculating the utilization rate is:

[0103]

[0104] Where N is the total number of guided telescopes in the scheme, and time j The operating time of the j-th guided telescope is time. all This represents the total duration of this observation.

[0105] The total duration of this observation includes all stages of the relay mission, starting at [time]. Figure 1 The moment when the central control system issues the relay task to the guided telescope. The total observation time does not include the working time of the guiding telescope.

[0106] In this embodiment, the guided device is simply used as a precision telescope. j Only the operating time of the precision telescope is considered. In other embodiments, if the general survey telescope is involved in guidance and makes a significant contribution to joint orbit determination, its participation in the utilization calculation needs to be considered.

[0107] Observation effectiveness: Observation effectiveness is a higher-level indicator than relay capability, orbit determination capability, and utilization rate, and is used to evaluate the observation effectiveness of a scheme.

[0108] Step S2: For each underlying indicator in the basic indicators, first map each data of the underlying indicator to a set of evaluation levels, then count the set of evaluation levels to which all data of the underlying indicator belong to obtain the basic assignment function of each set of evaluation levels as the membership degree, and combine them to obtain the membership degree vector of the underlying indicator.

[0109] In other words, step S2 uses the membership function method to standardize the data. First, the data is rated, and then the basic assignment function (i.e., membership degree) is statistically obtained based on the rating results. The membership degrees of different rating levels are combined to obtain a membership degree vector. Based on the data from multiple telescope combination schemes obtained in step S1 across multiple tasks, they can be rated. Each underlying indicator has a corresponding evaluation function that maps the data of that underlying indicator to an evaluation level. One purpose of step S2 is to obtain this evaluation level. Subsequently, since each task can assign an evaluation level to each underlying indicator of the telescope combination scheme, the membership degree of each underlying indicator can be obtained by statistically analyzing the evaluation levels across multiple tasks.

[0110] The evaluation levels are divided into "Good", "Medium", and "Poor". However, due to the inherent ambiguity in the reliability of the evaluation criteria and data, mapping each data point of the underlying indicators to a set of evaluation levels means mapping the data of the underlying indicators to elements of the power set of evaluation levels: {{Good}, {Good,Medium}, {Medium}, {Medium,Poor}, {Poor}, {Good,Medium,Poor}}. Each element of this power set represents a set of evaluation levels. In this embodiment, the letters "ABC" represent the evaluation levels "Good,Medium,Poor", and the evaluation level identification framework Θ is represented as Θ = {A,B,C}. The power set of evaluation levels can be represented as the set of all subsets of the identification framework, i.e., {{A},{A,B},{B},{B,C},{C},{A,B,C}}. The set of evaluation levels includes {A},{A,B},{B},{B,C},{C},{A,B,C}.

[0111] Therefore, for each top-level indicator, the power set of evaluation levels

[0112] The possible values ​​of the basic assignment function for each element in {{A},{A,B},{B},{B,C},{C},{A,B,C}} are the proportions of its power set index to a certain evaluation set within the identification framework Θ of that evaluation level.

[0113] For example, consider the following formula for the basic allocation function:

[0114]

[0115] The formula indicates that the basic allocation functions for the set of evaluation levels corresponding to the underlying indicator, {A}, {A,B}, {B}, {B,C}, {C}, {A,B,C}, are 0.2, 0.05, 0.5, 0.05, 0.1, and 0.1, respectively.

[0116] All underlying indicators are divided into quantitative and qualitative indicators. The method for mapping quantitative indicators to a set of evaluation levels is to use an evaluation function to rate different data points of the underlying indicators. The method for mapping qualitative indicators to a set of evaluation levels is to first perform quantile normalization on the different data points of the underlying indicators and then use the evaluation function to rate them. Quantile normalization is a normalization method that preserves data ranking and makes the data present a uniform distribution.

[0117] As mentioned above, the underlying metrics include deviation, response interval, relay success rate, track determination accuracy, track determination arc length, and utilization rate. In this embodiment, the quantitative metrics include deviation and track determination accuracy, while the qualitative metrics include response interval, relay success rate, track determination arc length, and utilization rate.

[0118] The specific method for mapping each data point of each underlying indicator to a set of evaluation levels is as follows.

[0119] Deviation: A quantitative indicator, considering that finding the target within 3 standard deviations of the guiding data is acceptable, finding it within 1 standard deviation is good, and finding it more than 3 standard deviations is poor. Therefore, the evaluation function v1(x1) for deviation x1 is:

[0120]

[0121] Response interval: A qualitative indicator, where the data validity period is longer than the successful bootstrapping interval. Therefore, a longer bootstrapping interval indicates a longer data validity period, but the converse is false. The first 20% of long validity periods are rated "good," the first 20% to 50% are rated "medium," and the remaining ones are rated "poor." Corresponding to the response interval, the rating is adjusted to "good," "good or medium," or "uncertain." The evaluation function for the response interval, v2(x2), is:

[0122]

[0123] Where x2 is the quantile normalization result of the response interval data, and v2(x2) is the evaluation function of the response interval.

[0124] Relay success rate: A qualitative indicator, with a higher success rate considered better. Therefore, the top 20% is rated "good," 20% to 50% is rated "average," and the remainder is rated "poor." Furthermore, the boundary between "good" and "average" is fuzzy, with an estimated 15% quantile ambiguity; the data also exhibits randomness, with an estimated 5% quantile ambiguity. Thus, the evaluation function v3(x3) for the relay success rate is:

[0125]

[0126] Where x3 is the quantile normalization result of the relay success rate data, and v3(x3) is the evaluation function of the relay success rate.

[0127] Track determination accuracy: a quantitative indicator. Since combined track determination requires higher accuracy than single-device track determination, an accuracy within 0.5 km is considered good, within 2 km is acceptable, and beyond 2 km is unacceptable. Therefore, the evaluation function for track determination accuracy, v4(x4), is:

[0128]

[0129] Where x4 represents the orbit determination accuracy, and v4(x4) is the evaluation function for orbit determination accuracy.

[0130] Orbit determination arc length: A qualitative indicator; the shorter the arc length, the stronger the timeliness of the data. Therefore, the top 20% are rated "good," 20% to 50% are rated "medium," and the rest are rated "poor." Furthermore, the relationship between arc length and accuracy is complex; there are cases where changes in arc length do not affect the evaluation of other indicators, leading to a 5% quantile ambiguity. Therefore, the evaluation function v5(x5) for orbit determination arc length is:

[0131]

[0132] Where x5 is the quantile normalization result of the orbital arc length data, and v5(x5) is the evaluation function for the orbital arc length.

[0133] Utilization rate: A qualitative indicator; the lower the utilization rate, the lower the evaluation of other indicators compared to the true rating of full-load capacity. Therefore, the top 20% is rated "good," 20% to 50% is rated "medium," and the remainder is rated "poor." However, utilization rate also reflects the rationality of the telescope configuration in the plan. Thus, the evaluation function for utilization rate, v6(x6), is...

[0134]

[0135] Where x6 is the quantile normalized result of the usage rate, and v6(x6) is the evaluation function of the usage rate.

[0136] Step S3: As Figure 3As shown, based on the DS evidence theory, starting from the bottom-level indicators, the basic indicators of the lower level are aggregated to obtain the membership vector of the basic indicators of the upper level, until the membership vector R of the top-level basic indicators is obtained.

[0137] The specific form of the membership vector R of the top-level basic index is as follows:

[0138]

[0139] Where m({A}), m({A,B}), m({B}), m({B,C}), m({C}), and m({A,B,C}) are the basic allocation functions of the sets of evaluation levels {A}, {A,B}, {B}, {B,C}, {C}, and {A,B,C} corresponding to the top-level basic indicators.

[0140] The membership vector R of the top-level basic index estimates the distribution of the evaluation level of the telescope combination scheme in practical applications. For example, if the membership of a telescope combination scheme in evaluation level B is 50%, then in most tasks, the performance of this telescope combination scheme is most likely to be in the middle position of the performance of all schemes in the database.

[0141] The method of this invention is based on DS evidence theory. As an uncertain reasoning method, evidence theory has the ability to directly express "uncertainty" and "not knowing," making it suitable for the basic indicators in this invention. The indicator aggregation method of this invention is based on DS evidence theory. Based on this prior art, the orthogonal sum formula for the probability m(A) of the upper-level basic indicators belonging to the set A of evaluation levels is:

[0142]

[0143] Where m is the basic allocation function of the basic indicators of the upper layer, m1, m2, ..., m n Let m(A) be the basic allocation function of the lower-level basic indicators, where m(A) represents the probability that the upper-level basic indicators belong to the set A of evaluation levels, and n is the number of lower-level basic indicators, A1, A2, ..., A1. n This represents the set to which the lower-level basic indicators belong. The denominator is called the evidence consistency degree, which serves as a normalization function, ensuring that the sum of the membership degrees in the aggregated membership degree vector of the upper-level indicators equals 1.

[0144] The orthogonal summation formula satisfies the commutative and associative laws, and the associative rate allows top-level indicators (such as observational effectiveness) to be directly aggregated from bottom-level indicators. However, this simplification cannot be achieved in this invention because the aggregation formula of this invention adds weight allocation coefficients on top of this.

[0145]

[0146] Where W is the weighting coefficient of the lower-level indicators of full-load observation efficiency I (i.e., observation efficiency I1 and utilization rate I2), and W1 is the lower-level indicator of observation efficiency I1 (i.e., relay capacity I). 1.1 and orbit determination capability I 1.2 The weighting coefficients, W 1.1 For relay ability I 1.1 The lower-level indicators (i.e., guidance capability I) 1.1.1 and relay success rate I 1.1.2 The weighting coefficients, W 1.2 For orbit determination capability I 1.2 The lower-level indicators (i.e., orbit determination accuracy I) 1.2.1 and orbital arc length I 1.2.2 The weighting coefficients, W 1.1.1 To guide capability I 1.1.1 The lower-level indicator (i.e., deviation I) 1.1.1.1 and response interval I 1.1.1.2 The weighting coefficients of ).

[0147] The weights and corresponding indicators in the indicator chart have the same subscript, such as relay ability I. 1.1 The weighting coefficient W of the lower-level indicators 1.1 Corresponding relay ability I 1.1 This describes the weighting of the basic indicators at the lower level. The weighting coefficients are used to adjust the proportion of membership.

[0148] Therefore, step S3 specifically includes:

[0149] Step S31: Modify the aggregation formula using the weight allocation coefficients of the lower-level indicators to obtain the aggregation formula of the upper-level basic indicators.

[0150] After revision, the aggregation formula for the basic indicators at the upper level is as follows:

[0151]

[0152] Where m is the basic allocation function of the upper-level basic indicators, m(A) represents the probability that the upper-level basic indicators belong to the set A of evaluation levels, i = 1 to n, n is the number of lower-level basic indicators, and A represents the set to which the upper-level basic indicators belong. i It is the basic allocation function of the lower-level basic indicators, A i ω represents the set to which the lower-level basic indicators belong. i It is the weighting coefficient of the lower-level indicators.

[0153] The denominator is the sum of the unnormalized membership degrees of the upper-level indicators, which is called the evidence consistency degree. It plays a normalization role, making the sum of membership degrees in the aggregated membership degree vector of the upper-level indicators equal to 1.

[0154] Step S32: Using the aggregation formula in step S31, starting from the lowest level of basic indicators, aggregate the basic indicators of the lower level to obtain the membership vector of the basic indicators of the upper level, until the membership vector of the top level basic indicators is obtained.

[0155] Since weighted aggregation methods lose the associative property, each index level must be calculated sequentially.

[0156] Step S4: Determine the score of the telescope combination scheme based on the membership vector R and performance weight of the top-level basic index obtained in Step S3; evaluate the performance of different telescope combination schemes based on the score, and the higher the score, the better the performance of the telescope combination scheme.

[0157] The effectiveness of the observation scheme is the top-level indicator among the basic indicators, and its membership vector R is obtained by aggregating the indicators layer by layer.

[0158] Performance weight W R The goal is to rank telescope combination schemes based on specific mission requirements, and to weight the performance W used for different missions. R Different. The performance weight W corresponding to the membership vector R of the top-level basic indicator. R Users can preset or adjust the parameters according to task requirements to weight the membership vector R of the top-level basic indicators and obtain a quantitative score.

[0159] In this embodiment, if only a moderately effective and stable solution needs to be selected to perform daily tasks, then the performance weight W... R Take [1, 1, 1, 0, 0, 0]; if a task is very challenging, and the telescope combination scheme must have at least a special advantage to succeed, then the efficiency weight W is [1, 1, 1, 0, 0, 0]. R We can choose [1, 1 / 2, 0, 0, 0, 1 / 3], using the efficiency weight W. R The weighted result is that the solution performs significantly better than the expected performance of at least 80% of the solutions in the library in this task, and the superiority or inferiority of the solution is judged by this expectation.

[0160] Step S4 also includes: after evaluating the effectiveness of different telescope combination schemes, performing the following operations based on the evaluation results: guiding the site selection of newly built guiding or guided telescopes based on the scores; selecting the telescope combination scheme with the best performance based on the scores.

[0161] 1) Guiding the selection of new site locations. For example, if there are 20 candidate sites, simulation is needed to compare their advantages and disadvantages before actual operation. The simulation method is to construct a series of observation tasks and telescope combination schemes, collect data from the observation tasks, and calculate the membership degree of each scheme. The final membership degree is the membership degree of the telescope combination scheme that includes the hypothetical site at the new location. After classifying the tasks, it is possible to predict in which aspects the new site selection will improve the current observation network.

[0162] 2) Selecting the most efficient telescope combination scheme. An observation network is not simply the sum of multiple telescopes operating independently; it includes joint observations with different baseline lengths. Currently, this invention attempts to select a better telescope combination scheme through an evaluation method. Looking further ahead, real-time scheduling of the entire observation network is the ultimate goal. However, currently, my country's research on the effectiveness of joint telescope observations is still in the early exploratory stage, primarily relying on simulation. Therefore, methods for evaluating the effectiveness of multiple telescope combinations are almost nonexistent in this field, and the evaluation method of this invention fills this gap.

[0163] Accordingly, step S32 may further include: in each process of aggregating the lower-level basic indicators to obtain the upper-level basic indicators, multiplying and summing the membership degrees of the lower-level basic indicators to obtain the sum of the unnormalized membership degrees of the upper-level basic indicators as the evidence consistency degree of the upper-level basic indicators.

[0164] Step S4 further includes: determining whether there are significant defects in the basic indicators of each telescope combination scheme based on the consistency of evidence for each basic indicator at the upper level; and guiding the improvement of the site facilities of the guiding or guided telescopes based on the consistency of evidence.

[0165] This invention can guide improvements to the site facilities of guiding or guided telescopes. By analyzing the consistency attributes of aggregated basic indicators, this invention can identify fundamental indicators with significant defects in telescope combination schemes, thereby guiding the improvement of hardware and software at certain sites within the scheme.

[0166] Among them, the consistency of evidence at each level can reflect whether the telescope combination scheme has significant defects in some basic indicators. The lower the consistency of evidence, the more significant the defects in the basic indicators.

[0167] Specifically, the greater the difference in evaluation between different indicators within the indicator layer, the lower the consistency of evidence. Since quantile normalization is used, the membership degree of an indicator essentially represents its ranking among all schemes. Therefore, it can be assumed that schemes with low consistency have certain performance deficiencies, allowing for further analysis of the merits of two telescope combination schemes with similar performance evaluations.

[0168] The formula for calculating the consistency of evidence is:

[0169]

[0170] However, some indices are inherently conflicting and can affect the judgment of scheme defects. For example, the shorter the orbit determination time for the same scheme in the same task, the lower the orbit determination accuracy. When a set of tasks is repeated multiple times, the distribution of the evidence consistency of the indicator layer containing the inherently conflicting indicators changes with the distribution of one of the indicators, thus exhibiting greater randomness; while the evidence consistency of the indicator layer containing the defective indicators will concentrate around a certain low value.

[0171] To eliminate the erroneous information caused by these inherently conflicting indicators, the hierarchical structure of the basic parameters involved in this invention combines obviously conflicting indicators into a separate indicator layer, namely the lower-level indicator layer of the two basic indicators of guidance capability and orbit determination capability, and excludes the situation where these two basic indicators are judged as significant defects due to a random decrease in the consistency of evidence.

[0172] Step S4 further includes: calculating and determining the similarity of different telescope combination schemes based on the membership vector of the top-level basic indicators of different telescope combination schemes, and determining whether the weight allocation coefficients of the lower-level indicators need to be adjusted based on the task completion degree of different telescope combination schemes in the actual task.

[0173] For different tasks, the evaluation method allows for the use of different weighting coefficients ω for lower-level indicators. i The weighting coefficient ω of the lower-level indicators i Whether the set value is reasonable needs to be verified afterward.

[0174] Theoretically, the greater the similarity of the membership vectors of the top-level basic indicators of two telescope combination schemes, the more likely the two schemes are to exhibit the same performance in tasks corresponding to different performance weights. Therefore, if this conclusion is contradicted in actual tasks, it indicates that the weight allocation coefficients of the current lower-level indicators need to be adjusted.

[0175] The similarity between different telescope combination schemes is determined using a similarity formula, which is:

[0176]

[0177] Where m1(A1) and m2(A2) are the basic assignment functions of the membership vectors for the performance evaluation of the first and second telescope combination schemes, respectively, and A1 and A2 are the sets of evaluation levels for the first and second telescope combination schemes, respectively. The denominator of the formula is for normalization purposes.

[0178] like Figure 4As shown, in another embodiment, the basic metrics are scalable, thereby making the evaluation method of the present invention scalable. The basic metrics include event analysis success rate set at the same level as full-load observation performance, event analysis capability located above full-load observation performance and event analysis success rate, and the number of features located below full-load observation performance, to expand the basic metrics.

[0179] Therefore, by extending the indicators as relevant and basic indicators for specific events, a new top-level indicator for event analysis capability is derived. The basic indicator feature number, which is related to equipment but not to the event itself, plays an important role in event analysis. Thus, compared to the original indicator chart, the meaning of full-load observation effectiveness has slightly changed to better meet the requirements.

[0180] The above description is merely a preferred application example of the present invention and is not intended to limit the present invention in any way. Those skilled in the art can make various equivalent changes and improvements based on the above embodiments, and all equivalent changes or modifications made within the scope of the claims should fall within the protection scope of the present invention.

Claims

1. A method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets, characterized in that, include: Step S1: During the operation of the telescope combination scheme, sample and obtain the underlying basic index data; Step S2: For each underlying indicator in the basic indicators, first map each data of the underlying indicator to a set of evaluation levels, then count the set of evaluation levels to which all data of the underlying indicator belong to obtain the basic assignment function of each set of evaluation levels as the membership degree, and combine them to obtain the membership degree vector of the underlying indicator. Step S3: Based on the DS evidence theory, starting from the bottom-level indicators, the indicators are aggregated to obtain the membership vector of the upper-level basic indicators, until the membership vector of the top-level basic indicators is obtained. Step S4: Determine the score of the telescope combination scheme based on the membership vector R and performance weight of the top-level basic index obtained in Step S3; evaluate the performance of different telescope combination schemes based on their scores, with higher scores indicating better performance. The basic indicators include the full-load observation efficiency at the top level, the observation efficiency and utilization rate at the lower level of full-load observation efficiency, the relay capability and orbit determination capability at the lower level of observation efficiency, the guidance capability and relay success rate at the lower level of relay capability, the orbit determination accuracy and orbit determination arc length at the lower level of orbit determination capability, and the deviation and response interval at the lower level of guidance capability.

2. The method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets according to claim 1, characterized in that, In step S1, the formula for calculating the deviation is: P is the decomposition matrix of the two-dimensional covariance of the location distribution represented by the guiding data. is the distance vector from the target observed by the guided telescope to the center of the guiding position; The formula for calculating the response interval is: t 2，i，Y，T -max X {t 1，i，x |T}, Among them, t 1,i,X t is the time when the X-guided telescope receives the observation data returned by its measuring equipment during the i-th phase of the mission. 2,i,Y,T The moment when the controller of guided telescope Y issues an observation request to target T during the i-th phase of the mission, where i is the mission phase number, X is the ordinal number of the guiding telescope, Y is the ordinal number of the guided telescope, T is the ordinal number of the target, and max X {t 1,i,X |T} is the last moment when all the guiding telescopes receive the observation data containing target T returned by their measuring instruments during the i-th phase of the mission; The formula for calculating the success rate of a relay race is: Among them, Quest number Quest represents the total number of times all relay missions have been issued. victory The number of successful relay missions; Orbit determination accuracy refers to the precision of the orbit determination result obtained from all observation data from a single target of the guided telescope; The formula for calculating the fixed-track arc length is: max Y {t 3，i，Y，T }-min i，X {t 1，i，X，T }, In the formula, t 3,i,Y,T The max value represents the moment when the central control receives observation data or failure information about target T sent back by the guided telescope Y during the i-th phase of the mission. Y {t 3,i,Y,T } is the last moment in phase i of the mission when all guided telescopes send back observation data or failure information about target T. 1,i,X,T It is the moment, min, when the X-guide telescope receives the observational data containing target T returned by its measuring equipment during mission phase i. i,X {t 1,i,X,T } is the earliest moment when all guiding telescopes receive observational data containing target T returned by their measuring equipment at all mission phases; The formula for calculating utilization rate is: Where N is the total number of guided telescopes in the scheme, and time j The operating time of the j-th guided telescope is time. all This represents the total duration of this observation.

3. The method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets according to claim 1, characterized in that, In step S2, mapping each data point of the underlying indicator to the set of evaluation levels means mapping the data of the underlying indicator to the elements of the power set of evaluation levels {{good}, {good, medium}, {medium}, {medium, poor}, {poor}, {good, medium, poor}}, where each element of the power set represents a set of evaluation levels. All underlying indicators are divided into quantitative indicators and qualitative indicators. The method of mapping quantitative indicators to the set of evaluation levels is to use an evaluation function to rate the different data of the underlying indicators. The method of mapping qualitative indicators to the set of evaluation levels is to first perform quantile normalization on the different data of the underlying indicators and then use an evaluation function to rate them. and / or In step S3, the membership vector R of the top-level basic index is obtained in the following specific form: Where m({A}), m({A,B}), m({B}), m({B,C}), m({C}), and m({A,B,C}) are the basic allocation functions of the sets {A}, {A,B}, {B}, {B,C}, {C}, and {A,B,C} corresponding to the top-level basic indicators, respectively. A, B, and C represent good, average, and poor, respectively.

4. The method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets according to claim 3, characterized in that, The quantitative indicators include deviation and orbit determination accuracy, while the qualitative indicators include response interval, relay success rate, orbit determination arc length, and utilization rate.

5. The method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets according to claim 2, characterized in that, The guiding telescope is a general survey telescope, and the guided telescope is a precision survey telescope.

6. The method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets according to claim 1, characterized in that, Step S3 specifically includes: Step S31: Modify the aggregation formula using the weight allocation coefficients of the lower-level indicators to obtain the aggregation formula of the upper-level basic indicators. After revision, the aggregation formula for the basic indicators at the upper level is as follows: Where m is the basic allocation function of the upper-level basic indicators, m(A) represents the probability that the upper-level basic indicators belong to the set A of evaluation levels, i = 1 to n, n is the number of lower-level basic indicators, and A represents the set to which the upper-level basic indicators belong. i It is the basic allocation function of the lower-level basic indicators, A i ω represents the set to which the basic indicators of the lower level belong. i It is the weighting coefficient of the lower-level indicators; Step S32: Using the aggregation formula in step S31, starting from the lowest level of basic indicators, aggregate the basic indicators of the lower level to obtain the membership vector of the basic indicators of the upper level, until the membership vector of the top level basic indicators is obtained.

7. The method for evaluating the collaborative tracking performance of high-low combination telescopes for GEO targets according to claim 6, characterized in that, The weighting coefficients for the lower-level indicators include: W＝[0.7，0.3] W1＝[0.5，0.5] W 1.1 ＝[0.5，0.5] W 1.2 ＝[0.6，0.4] W 1.1.1 ＝[0.6，0.4] Where W is the weight allocation coefficient of the lower-level indicators of full-load observation efficiency, and W1 is the weight allocation coefficient of the lower-level indicators of observation efficiency. 1.1 W is the weighting coefficient for the lower-level indicators of relay capability. 1.2 W is the weighting coefficient for the lower-level indicators of orbit determination capability. 1.1.1 Weighting coefficients for lower-level indicators of guiding capability; and / or The performance weights corresponding to the membership vectors of the top-level basic indicators are preset or adjusted by the user according to task requirements.

8. The method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets according to claim 1, characterized in that, Step S4 further includes: after evaluating the effectiveness of different telescope combination schemes, performing the following operations based on the evaluation results: guiding the site selection of newly built guiding or guided telescopes based on the scores; selecting the telescope combination scheme with the best performance based on the scores.

9. The method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets according to claim 6, characterized in that, Step S32 further includes: in each process of aggregating the lower-level basic indicators to obtain the upper-level basic indicators, multiplying and summing the membership degrees of the lower-level basic indicators to obtain the sum of the unnormalized membership degrees of the upper-level basic indicators as the evidence consistency degree of the upper-level basic indicators; and step S4 further includes: judging whether there are significant defects in the upper-level basic indicators of each telescope combination scheme based on the evidence consistency degree of each upper-level basic indicator; guiding the improvement of the site facilities of the guiding or guided telescopes based on the evidence consistency degree; and / or Step S4 further includes: calculating and determining the similarity of different telescope combination schemes based on the membership vector of the top-level basic indicators of different telescope combination schemes, and determining whether the weight allocation coefficients of the lower-level indicators need to be adjusted based on the task completion degree of different telescope combination schemes in the actual task.

10. The method for evaluating the collaborative tracking performance of high-low array telescopes for GEO targets according to claim 1, characterized in that, The basic metrics also include the event analysis success rate, which is set at the same level as the full-load observation performance; the event analysis capability, which is located above the full-load observation performance and the event analysis success rate; and the number of features, which is located below the full-load observation performance.

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