A measurement, control, digital transmission, rocket and remote control integrated optimization method and system

Abstract

The invention discloses a measurement, control, data transmission, rocket and remote sensing integrated optimization method and system, which specifically relates to the field of satellite measurement and control technology, including step S001, recording a task set as R, determining the type of task, matching antenna and time window through identification information before each task; step S002, obtaining time constraint conditions: based on the time window and expected completion time of each task, obtaining the constraint conditions of the task as Yt; step S003, obtaining antenna constraint conditions: obtaining the matching degree between each task and each antenna; step S004, obtaining task allocation strategy: based on constraint conditions and particle swarm algorithm, first randomly generating N kinds of task allocation strategies, considering the processing scheme as the input of the particle swarm algorithm model, determining the population position and speed, iterating based on the constraint conditions, and obtaining the optimal task allocation strategy as the task strategy to be executed; step S005, monitoring the execution of the task: executing the task strategy, calculating the completion rate of the task and the task strategy yield.

Description

Technical Field

[0001] The present invention relates to the field of satellite measurement and control technology, and more specifically, to a measurement and control, digital transmission, rocket and remote control integrated optimization method and system. Background Art

[0002] With the rapid development of my country's aerospace industry, satellites are gradually turning to commercial development. The difference between the commercial development of satellites and their militarization is that commercial satellites do not have the conditions to support a large number of equipment and need to use limited equipment to complete different tasks. The resource problems and high cost problems of the ground measurement and control network are becoming increasingly prominent. Realizing the integration of measurement and control, digital transmission, rocket and remote sensing is one of the effective ways to solve the above problems.

[0003] In order to realize the commercial development of satellites, satellite ground stations need a simple measurement, control, digital transmission, and remote sensing mission processing system to maximize the benefits of mobilizing ground resources.

[0004] Traditional satellite measurement and control, data transmission, and rocket telemetry belong to different systems, which are complex in design and occupy a lot of resources, which is not conducive to the integrated and simplified design with microsatellites. Although there are certain differences in measurement and control tasks, data transmission tasks, and rocket telemetry tasks, the commonality of the three is that they are all based on antenna reception tasks, so they have an important prerequisite for integration. However, the current satellite ground stations do not have the ability to work in time-sharing, and cannot realize the unified processing of satellite measurement and control, data transmission and rocket telemetry tasks. In the satellite ground, the equipment resources in the satellite ground station are limited, and the benefits of measurement and control, data transmission, and rocket telemetry mission execution cannot be maximized. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an integrated optimization method and system for measurement, control, digital transmission, and remote sensing. By establishing a resource scheduling model for measurement and control, digital transmission, and remote sensing, the optimal task strategy is obtained by evaluating the value of the task strategy to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: a measurement and control data transmission and remote control integrated optimization method, such as Figure 1 As shown, the task allocation optimization process including the measurement and control task, the data transmission task and the arrow remote control task includes the following steps:

[0007] Step S001, record the task set as R, the tasks include rocket telemetry tasks, satellite measurement and control tasks, and data transmission tasks. Before each task, the type of task, matching antenna, and time window are determined through identification information;

[0008] Step S002: Based on the time window and expected completion time of each task, the constraint condition of the task is obtained as Yt;

[0009] Step S003, obtaining the matching degree pij between each task and each antenna;

[0010] Step S004: Based on the constraints and the particle swarm algorithm, N kinds of task allocation strategies are randomly generated first, the processing scheme is regarded as the input of the particle swarm algorithm model, the population position and speed are determined, and it is iterated based on the constraints to obtain the optimal task allocation strategy as the task strategy to be executed;

[0011] Step S005: Execute the task strategy and calculate the task completion rate and task strategy yield.

[0012] Preferably, in step S004, the iteration process of the particle swarm algorithm includes an evaluation unit for the task allocation strategy, and the evaluation unit for the task allocation strategy is used to evaluate the comprehensive value Zp of the task strategy, including the following steps:

[0013] Step S01, obtaining the target completion degree of each task in the task strategy, wherein the completion degree Wcd is used to represent the target completion degree of the task, and the actual completion amount of the task is compared with the overall amount of the task;

[0014] Step S02, find the historical optimal score G of each task in the task allocation strategy, set the historical optimal score of each task to be G1, G2, ..., Gn, obtain the score ji of each task in the task allocation strategy, recorded as j1, j2, ..., jn;

[0015] Step S03: Calculate the distance between each task in the task strategy and the task corresponding to the historical best score, obtain the comprehensive value of each task allocation, and satisfy the formula ;

[0016] Step S04, assume that the particle swarm algorithm obtains m task strategies, and the comprehensive value of each task strategy is recorded as Zp1, Zp2, ..., Zpm, and MAXZpi is taken as the task strategy to be executed.

[0017] Preferably, the completion degree Wcd includes the target completion degrees of the data transmission task, the arrow remote control task and the measurement and control task, wherein the completion degree Wcd of the data transmission task is [0.1-1], and the calculation method is , where sc represents the actual completion of the data transmission task, SC0 represents the target completion of the data transmission task, t0 represents the minimum connection time of the data transmission task, Ssc represents the transmission distance of the data transmission task, Vsc represents the transmission speed of the data transmission task, and the completion degree of the arrow remote control task and the measurement and control task is [0,1].

[0018] Preferably, the ji satisfies If the task is not completed, that is, Wcd=0, that is, ji=0, the larger the Zp, the more reasonable the task allocation, where c1 is the precision correction constant, Ki is the inherent value of the task, and Pi is the probability of successful execution of the task. Pi is obtained based on big data statistics. When Wcd=1, ji=G, that is, the historical optimal score G of each task in the task allocation strategy, satisfies , where pij identifies the matching degree between the task and the antenna, i takes the value of [1,2,3,], j takes the value of [1-k], and the equipment matching degrees of satellite measurement and control, rocket telemetry, and data transmission tasks are recorded as Ys1=[p11*tx1,p12*tx2,…,p1k*txk], Ys2=[p21*tx1,p22*tx2,…,p2k*txk], Ys3=[p31*tx1,p32*tx2,…,p3k*txk], where k types of antennas are recorded as TX=[tx1,tx2,…,txk].

[0019] Preferably, in step S004, in the particle swarm algorithm, when an irreversible conflict in the use of equipment resources occurs between a data transmission task and a measurement and control task or a remote sensing task, the data transmission task time is trimmed to try to arrange equipment for each task, including the following processes: obtaining important parameters in the data transmission task, screening out important parameters from data packets to be transmitted, obtaining small-volume data transmission data packets, obtaining new data transmission task time, caching the eliminated data transmission tasks, and waiting for idle time to send.

[0020] Preferably, in step S005, during the calculation of the task completion rate, Zji is used to indicate whether the task is executed. If the task is completed, zji=1; if the task is not completed, zji=0. ZL satisfies ,In the calculation process of the task strategy rate of return, the formula is satisfied , based on obtaining the three-dimensional task completion rate update.

[0021] To achieve the above object, the present invention provides the following technical solution: a measurement, control, digital transmission, rocket and remote integrated optimization system, used to implement a measurement, control, digital transmission, rocket and remote integrated optimization method as described in any one of claims 1 to 6, characterized in that it includes a satellite measurement and control management module, a rocket telemetry management module, a data transmission management module, a signal management module, and a task management module.

[0022] The satellite measurement and control management module is used to measure and control the satellite, collect satellite running speed and running trajectory information, and transmit the measurement and control data to the ground through the data transmission equipment, and compile the satellites that meet the conditions into the task set;

[0023] The rocket telemetry module is used to obtain rocket status information, and transmit telemetry data to the ground through a data transmission device, obtain telemetry accuracy and key parameters, establish a co-return multi-satellite serial constellation, increase the time window for satellites to receive rocket telemetry signals in a step tracking manner, mark the window set, and complete the capture and tracking of the target based on the direction of the incoming wave signal estimated by the two-dimensional direction finding algorithm of the phased array antenna;

[0024] The data transmission management module is used to adjust the angle of the data receiving and sending equipment, obtain the signals transmitted by the rocket and the satellite, and transmit the collected signals to the signal management module. The data transmission management module includes an arrow-to-satellite data transmission management unit and a satellite-to-ground data transmission management unit. The arrow-to-satellite data transmission management unit monitors the position and trajectory of the rocket by managing the satellite antenna, monitors the rocket by presetting the rocket trajectory, obtains the rocket telemetry signal, and assumes that the obtained signal is f1, and obtains a signal with a frequency of f2 after signal modulation; the satellite-to-ground data transmission management unit is used to transmit the frequency f2 signal to the ground receiving point, and the ground receiving point obtains the signal through the antenna;

[0025] The signal management module includes a signal modulation unit, a signal analysis unit and a signal storage unit, wherein the signal analysis unit obtains identification information in the signal, obtains a project task of the signal based on the identification information, and transmits the task project to the task management module;

[0026] The task management module is used to manage the acquired tasks, match the task execution equipment to the tasks based on the optimal equipment and time constraints of the tasks, and includes a resource scheduling unit and a task evaluation unit. The task evaluation unit is used to evaluate the completion degree of the tasks and the yield of the allocation strategy, and change the task based on the completion degree of the tasks and the yield of the allocation strategy.

[0027] Preferably, the task management module includes a constraint acquisition unit, a task allocation strategy acquisition unit and a task allocation strategy evaluation unit. The constraint acquisition unit is used to acquire time constraints and equipment constraints of the task, and the equipment constraints include antenna constraints; the task allocation strategy acquisition unit uses a particle swarm algorithm to acquire the optimal task allocation strategy based on the acquired constraints; the task strategy evaluation unit is used to evaluate the execution effect of the task strategy, and use the execution effect to evaluate the effect of the integrated optimization method of measurement, control, digital transmission, rocket and remote control.

[0028] Preferably, the constraint condition unit includes data transmission task constraints, measurement and control task constraints and remote sensing task constraints, among which the time constraints in the data transmission task constraints are flexible constraints. According to the importance of data in the data transmission task, the data is divided into urgent data and non-urgent data. When the data transmission task is only used to transmit urgent tasks, the use of resources can be reduced.

[0029] Technical effects and advantages of the present invention:

[0030] The present invention specifically obtains the constraint conditions of the measurement, control, digital transmission, rocket and remote control tasks, and uses the particle swarm algorithm to obtain the task allocation strategy. By providing a value evaluation method for the task strategy, the optimal task allocation strategy is obtained. In the task allocation, flexible constraint conditions are set to ensure that more tasks are executed. By supervising the execution of the tasks, the execution effect of the tasks is obtained, and a numerical value of the task yield is provided to evaluate the effect of the optimization method, thereby solving the problem that the existing ground station cannot complete the tasks in time sharing when performing the measurement, control, digital transmission, rocket and remote control tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The figure is a flow chart of the method of the present invention.

[0032] Figure 2 This is a flow chart for evaluating the task allocation strategy of the present invention.

[0033] Figure 3 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] The terms "module", "system", etc. used in this application are intended to include computer-related entities, such as but not limited to hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a module can be, but is not limited to: a process running on a processor, a processor, an object, an executable program, a thread of execution, a program, and / or a computer. For example, an application running on a computing device and the computing device can both be modules. One or more modules can be located within a process and / or thread in execution, and a module can also be located on one computer and / or distributed between two or more computers.

[0036] Example 1

[0037] This embodiment provides Figure 1 The invention discloses an integrated optimization method for measurement, control, data transmission, and remote sensing, including a task allocation optimization process for measurement, control, data transmission, and remote sensing tasks, wherein the task allocation includes the following steps:

[0038] Step S001, record the task set as R=[r1, r2, r3, ..., rn], the tasks include rocket telemetry tasks, satellite measurement and control tasks, and data transmission tasks. Before each task, the type of task, matching antenna, and time window are determined by identification information;

[0039] Step S002, obtaining time constraints: based on the time window and expected completion time of each task, obtaining the task constraints Yt=[yt1, yt2, ..., ytn];

[0040] Step S003, obtaining antenna constraint conditions: there are k types of antennas, denoted as TX=[tx1, tx2, ..., txk], an antenna ki can only be connected to one satellite at any time, and the matching degree pij between each task and each antenna is obtained;

[0041] Step S004, obtaining the task allocation strategy: based on the constraint conditions and the particle swarm algorithm, first randomly generate N kinds of task allocation strategies, regard the processing scheme as the input of the particle swarm algorithm model, determine the population position and speed, iterate based on the constraint conditions, and obtain the optimal task allocation strategy as the task strategy to be executed;

[0042] Step S005, monitor the execution of the task: execute the task strategy, calculate the task completion rate and the task strategy yield.

[0043] like Figure 2 As shown, in step S004, the iteration process of the particle swarm algorithm includes an evaluation unit for the task allocation strategy, and the evaluation unit for the task allocation strategy is used to evaluate the comprehensive value Zp of the task strategy, including the following steps:

[0044] Step S01, obtaining the target completion degree of each task in the task strategy, wherein the completion degree Wcd is used to represent the target completion degree of the task, and the actual completion amount of the task is compared with the overall amount of the task;

[0045] Step S02, find the historical optimal score G of each task in the task allocation strategy, set the historical optimal score of each task to be G1, G2, ..., Gn, obtain the score ji of each task in the task allocation strategy, recorded as j1, j2, ..., jn;

[0046] Step S03, calculating the distance between each task in the task strategy and the task corresponding to the best historical score, and obtaining the comprehensive value of each task allocation;

[0047] Step S04, assume that the particle swarm algorithm obtains m task strategies, and the comprehensive value of each task strategy is recorded as Zp1, Zp2, ..., Zpm, and MAXZpi is taken as the task strategy to be executed.

[0048] Furthermore, the comprehensive value formula in step S03 satisfies .

[0049] Furthermore, the completion degree Wcd includes the target completion degree of the data transmission task, the arrow remote control task and the measurement and control task, wherein the completion degree Wcd of the data transmission task is [0.1-1], and the calculation method is , where sc represents the actual completion of the data transmission task, SC0 represents the target completion of the data transmission task, t0 represents the minimum connection time of the data transmission task, Ssc represents the transmission distance of the data transmission task, Vsc represents the transmission speed of the data transmission task, and the completion degree of the arrow remote control task and the measurement and control task is [0,1].

[0050] Furthermore, the ji satisfies If the task is not completed, that is, Wcd=0, that is, ji=0, the larger the Zp, the more reasonable the task allocation, where c1 is the precision correction constant, Ki is the inherent value of the task, and Pi is the probability of successful execution of the task. Pi is obtained based on big data statistics. When Wcd=1, ji=G, that is, the historical optimal score G of each task in the task allocation strategy, satisfies , where pij identifies the matching degree between the task and the antenna, i takes the value of [1,2,3,], j takes the value of [1-k], and the equipment matching degrees of satellite measurement and control, rocket telemetry, and data transmission tasks are recorded as Ys1=[p11*tx1,p12*tx2,…,p1k*txk], Ys2=[p21*tx1,p22*tx2,…,p2k*txk], Ys3=[p31*tx1,p32*tx2,…,p3k*txk], where k types of antennas are recorded as TX=[tx1,tx2,…,txk].

[0051] Furthermore, in step S004, in the particle swarm algorithm, when an irreversible conflict in the use of equipment resources occurs between the data transmission task and the measurement and control task or the remote sensing task, the data transmission task time is trimmed to try to arrange equipment for each task, including the following processes: obtaining important parameters in the data transmission task, screening out important parameters from the data packets to be transmitted, obtaining small-volume data transmission data packets, obtaining new data transmission task time, caching the eliminated data transmission tasks, and waiting for idle time to send them.

[0052] Furthermore, in step S005, during the calculation of the task completion rate, Zji is used to indicate whether the task is executed. If the task is completed, zji=1; if the task is not completed, zji=0. ZL satisfies ,In the calculation process of the task strategy rate of return, the formula is satisfied , based on obtaining the three-dimensional task completion rate update.

[0053] Example 2

[0054] To achieve the above purpose, Figure 3 As shown, the embodiment of the present invention provides the following technical solutions: a measurement, control, data transmission, rocket and telemetry integrated optimization system, including a satellite measurement and control management module, a rocket telemetry management module, a data transmission management module, a signal management module, and a task management module.

[0055] The satellite measurement and control management module is used to measure and control the satellite, collect satellite running speed and running trajectory information, and transmit the measurement and control data to the ground through the data transmission equipment, and compile the satellites that meet the conditions into the task set;

[0056] The rocket telemetry module is used to obtain rocket status information, and transmit telemetry data to the ground through a data transmission device, obtain telemetry accuracy and key parameters, establish a co-return multi-satellite serial constellation, increase the time window for satellites to receive rocket telemetry signals in a step tracking manner, mark the window set, and complete the capture and tracking of the target based on the direction of the incoming wave signal estimated by the two-dimensional direction finding algorithm of the phased array antenna;

[0057] The data transmission management module is used to adjust the angle of the data receiving and sending equipment, obtain the signals transmitted by the rocket and the satellite, and transmit the collected signals to the signal management module. The data transmission management module includes an arrow-to-satellite data transmission management unit and a satellite-to-ground data transmission management unit. The arrow-to-satellite data transmission management unit monitors the position and trajectory of the rocket by managing the satellite antenna, monitors the rocket by presetting the rocket trajectory, obtains the rocket telemetry signal, and assumes that the obtained signal is f1, and obtains a signal with a frequency of f2 after signal modulation; the satellite-to-ground data transmission management unit is used to transmit the frequency f2 signal to the ground receiving point, and the ground receiving point obtains the signal through the antenna;

[0058] The signal management module includes a signal modulation unit, a signal analysis unit and a signal storage unit, wherein the signal analysis unit obtains identification information in the signal, obtains a project task of the signal based on the identification information, and transmits the task project to the task management module;

[0059] The task management module is used to manage the acquired tasks, match the task execution equipment to the tasks based on the optimal equipment and time constraints of the tasks, and includes a resource scheduling unit and a task evaluation unit. The task evaluation unit is used to evaluate the completion degree of the tasks and the yield of the allocation strategy, and change the task based on the completion degree of the tasks and the yield of the allocation strategy.

[0060] Furthermore, the task management module includes a constraint acquisition unit, a task allocation strategy acquisition unit and a task allocation strategy evaluation unit. The constraint acquisition unit is used to acquire time constraints and equipment constraints of the task, and the equipment constraints include antenna constraints; the task allocation strategy acquisition unit uses a particle swarm algorithm based on the acquired constraints to acquire the optimal task allocation strategy; the task strategy evaluation unit is used to evaluate the execution effect of the task strategy, and use the execution effect to evaluate the effect of the integrated optimization method of measurement, control, digital transmission, rocket and remote sensing.

[0061] Furthermore, the constraint condition unit includes data transmission task constraints, measurement and control task constraints and remote sensing task constraints, among which the time constraints in the data transmission task constraints are flexible constraints. According to the importance of data in the data transmission task, the data is divided into urgent data and non-urgent data. When the data transmission task is only transmitted for urgent tasks, the use of resources can be reduced.

[0062] The embodiments of the present invention merely provide one implementation mode, rather than specifically limiting the protection scope of the present invention.

[0063] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A measurement, control, data transmission, and remote control integrated optimization method, including a task allocation optimization process for measurement and control tasks, data transmission tasks, and remote control tasks, characterized in that: The task allocation includes the following steps: Step S001, record the task set as R, the tasks include rocket telemetry tasks, satellite measurement and control tasks, and data transmission tasks. Before each task, the type of task, matching antenna, and time window are determined through identification information; Step S002, obtaining time constraints: based on the time window and expected completion time of each task, obtaining the task constraints Yt=[yt1, yt2, ..., ytn]; Step S003, obtaining antenna constraint conditions: there are k types of antennas, one antenna ki can only be interconnected with one satellite at any time, and the matching degree pij between each task and each antenna is obtained; Step S004, obtaining the task allocation strategy: based on the constraint conditions and the particle swarm algorithm, first randomly generate N kinds of task allocation strategies, regard the processing scheme as the input of the particle swarm algorithm model, determine the population position and speed, iterate based on the constraint conditions, and obtain the optimal task allocation strategy as the task strategy to be executed. The iterative process of the particle swarm algorithm includes an evaluation unit for the task allocation strategy, and the evaluation unit for the task allocation strategy is used to evaluate the comprehensive value Zp of the task strategy, including the following steps: Step S01, obtain the target completion degree of each task in the task strategy, the completion degree Wcd is used to represent the target completion degree of the task, and the actual completion amount of the task is compared with the overall amount of the task; Step S02, find the historical optimal score G of each task in the task allocation strategy, set the historical optimal score of each task to G1, G2, ..., Gn, obtain the score ji of each task in the task allocation strategy, recorded as j1, j2, ..., jn; Step S03, calculate the distance between each task in the task strategy and the task corresponding to the historical optimal score, obtain the comprehensive value of each task allocation, and satisfy the formula ; Step S04, assume that the particle swarm algorithm obtains m task strategies, and the comprehensive value of each task strategy is recorded as Zp1, Zp2, ..., Zpm, and MAXZpi is taken as the task strategy to be executed; Said ji satisfies If the task is not completed, that is, Wcd=0, that is, ji=0, the larger the Zp, the more reasonable the task allocation, where c1 is the precision correction constant, Ki is the inherent value of the task, and Pi is the probability of successful execution of the task. Pi is obtained based on big data statistics. When Wcd=1, ji=G, that is, the historical optimal score G of each task in the task allocation strategy, satisfies , where pij identifies the matching degree between the task and the antenna, i takes the value of [1,2,3,], j takes the value of [1-k], and the equipment matching degree of satellite measurement and control, rocket telemetry, and data transmission tasks are recorded as Ys1=[p11*tx1,p12*tx2,…,p1k*txk],Ys2=[p21*tx1,p22*tx2,…,p2k*txk],Ys3=[p31*tx1,p32*tx2,…,p3k*txk], where k types of antennas are recorded as TX=[tx1,tx2,…,txk]; Step S005, monitoring the execution of the task: executing the task strategy, calculating the task completion rate and the task strategy yield; In the calculation process of the task completion rate, Zji is used to indicate whether the task is executed. If the task is completed, zji=1; if the task is not completed, zji=0. ZL satisfies ,In the calculation process of the task strategy rate of return, the formula is satisfied , based on obtaining the three-dimensional task completion rate update.

2. The integrated optimization method for measurement, control, data transmission, and remote control according to claim 1 is characterized in that: The completion degree Wcd includes the target completion degree of the data transmission task, the arrow remote control task and the measurement and control task, wherein the completion degree Wcd of the data transmission task is [0.1-1], and the calculation method is , where sc represents the actual completion of the data transmission task, SC0 represents the target completion of the data transmission task, t0 represents the minimum connection time of the data transmission task, Ssc represents the transmission distance of the data transmission task, Vsc represents the transmission speed of the data transmission task, and the completion degree of the arrow remote control task and the measurement and control task is [0,1].

3. The integrated optimization method for measurement, control, data transmission, and remote control according to claim 1 is characterized in that: In the particle swarm algorithm, when an unadjustable conflict in the use of equipment resources occurs between a data transmission task and a measurement and control task or a remote sensing task, the data transmission task time is trimmed to try to arrange equipment for each task, including the following processes: obtaining important parameters in the data transmission task, screening out important parameters from data packets to be transmitted, obtaining small-volume data transmission data packets, obtaining new data transmission task time, caching the eliminated data transmission tasks, and waiting for idle time to send them.

4. A measurement, control, digital transmission, arrow and remote control integrated optimization system, used to implement a measurement, control, digital transmission, arrow and remote control integrated optimization method as described in any one of claims 1 to 3, characterized in that: Including satellite measurement and control management module, rocket telemetry management module, data transmission management module, signal management module, mission management module, The satellite measurement and control management module is used to measure and control the satellite, collect satellite running speed and running trajectory information, and transmit the measurement and control data to the ground through the data transmission equipment, and compile the satellites that meet the conditions into the task set; The rocket telemetry module is used to obtain rocket status information, and transmit telemetry data to the ground through a data transmission device, obtain telemetry accuracy and key parameters, establish a co-return multi-satellite serial constellation, increase the time window for satellites to receive rocket telemetry signals in a step tracking manner, mark the window set, and complete the capture and tracking of the target based on the direction of the incoming wave signal estimated by the two-dimensional direction finding algorithm of the phased array antenna; The data transmission management module is used to adjust the angle of the data receiving and sending equipment, obtain the signals transmitted by the rocket and the satellite, and transmit the collected signals to the signal management module. The data transmission management module includes an arrow-to-satellite data transmission management unit and a satellite-to-ground data transmission management unit. The arrow-to-satellite data transmission management unit monitors the position and trajectory of the rocket by managing the satellite antenna, monitors the rocket by presetting the rocket trajectory, obtains the rocket telemetry signal, and assumes that the obtained signal is f1, and obtains a signal with a frequency of f2 after signal modulation; the satellite-to-ground data transmission management unit is used to transmit the frequency f2 signal to the ground receiving point, and the ground receiving point obtains the signal through the antenna; The signal management module includes a signal modulation unit, a signal analysis unit and a signal storage unit, wherein the signal analysis unit obtains identification information in the signal, obtains a project task of the signal based on the identification information, and transmits the task project to the task management module; The task management module is used to manage the acquired tasks, match the task execution equipment to the tasks based on the optimal equipment and time constraints of the tasks, and includes a resource scheduling unit and a task evaluation unit. The task evaluation unit is used to evaluate the completion degree of the tasks and the yield of the allocation strategy, and change the task based on the completion degree of the tasks and the yield of the allocation strategy.

5. The integrated optimization system for measurement, control, data transmission, and remote control according to claim 4 is characterized in that: The task management module includes a constraint acquisition unit, a task allocation strategy acquisition unit and a task allocation strategy evaluation unit. The constraint acquisition unit is used to acquire the time constraints and equipment constraints of the task, and the equipment constraints include antenna constraints; the task allocation strategy acquisition unit uses a particle swarm algorithm based on the acquired constraints to acquire the optimal task allocation strategy; the task strategy evaluation unit is used to evaluate the execution effect of the task strategy, and use the execution effect to evaluate the effect of the integrated optimization method of measurement, control, digital transmission, rocket and remote control.

6. The integrated optimization system for measurement, control, data transmission, and remote control according to claim 5 is characterized by: The constraint unit includes data transmission task constraints, measurement and control task constraints and remote sensing task constraints. The time constraint in the data transmission task constraints is a flexible constraint. The scope of the data transmission task is narrowed according to the importance of the data in the data transmission task.

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