SAR (Synthetic Aperture Radar) imaging task planning and arranging method based on satellite energy strong constraint

Abstract

The invention relates to an SAR imaging task planning and arranging method based on satellite energy strong constraint, and the method comprises the following steps: S1, obtaining task information which comprises orbit parameter information, scene time, whole-satellite energy constraint requirements, load capability constraint requirements and a target task set; s2, based on the orbit parameter information, the scene time, the load capacity constraint requirement and the target task set, carrying out visibility calculation on an imaging target in the target task set; s3, based on the whole-satellite energy constraint requirement and the load capacity constraint requirement, in combination with an imaging task arrangement strategy, imaging target conflict resolution is completed, and an imaging window is determined through a rolling imaging window planning strategy; and S4, completing duration processing of the imaging window based on a load capacity constraint requirement, and outputting an imaging task arrangement result meeting a whole-satellite energy constraint requirement. According to the method, the imaging task planning and arrangement problem under the condition that the SAR imaging satellite is strongly constrained by energy is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of satellite application technology, and in particular to a SAR imaging mission planning and scheduling method based on strong satellite energy constraints. Background Art

[0002] SAR imaging technology is an all-day, all-weather, high-resolution radar imaging technology that is widely used in disaster monitoring, environmental monitoring, ocean monitoring, resource exploration, mapping and other fields. SAR imaging usually has a variety of imaging modes, including strip, spotlight, scanning, etc. With the development of current technology, SAR imaging technology is moving towards higher resolution, faster data processing speed and wider application.

[0003] With the increasing demand for ground imaging tasks, SAR imaging technology has significantly increased the requirements for satellite energy and computing power, which has greatly increased the pressure on the satellite energy subsystem. The satellite energy subsystem is an important subsystem to ensure the survival of the satellite. Therefore, satellite energy constraints are a strong constraint for satellites to perform on-orbit tasks. At present, satellite mission planning technology is an important way for satellites to achieve autonomous mission planning and scheduling. Energy constraints are a type of strong constraints on satellites, and mission planning technology is required to fully consider the constraints to achieve the planning and scheduling of SAR imaging tasks. Summary of the invention

[0004] In order to solve the technical problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a SAR imaging mission planning and scheduling method based on strong satellite energy constraints, which can effectively solve the imaging mission planning and scheduling problems of SAR imaging satellites under the condition of strong energy constraints.

[0005] To achieve the above-mentioned purpose, the present invention provides a SAR imaging mission planning and scheduling method based on strong satellite energy constraints, comprising the following steps:

[0006] Step S1, obtaining mission information, wherein the mission information includes orbit parameter information, scenario time, whole-satellite energy constraint requirements, payload capacity constraint requirements and target mission set;

[0007] Step S2, based on the orbital parameter information, the scene time, the load capacity constraint requirement and the target task set, performing visibility calculation on the imaging target in the target task set;

[0008] Step S3: Based on the energy constraint requirements of the entire satellite and the load capacity constraint requirements, combined with the imaging task scheduling strategy, complete the imaging target conflict resolution, and determine the imaging window through the rolling imaging window planning strategy;

[0009] Step S4: completing the duration processing of the imaging window based on the load capacity constraint requirement, and outputting the imaging task scheduling result that meets the energy constraint requirement of the entire satellite.

[0010] According to a technical solution of the present invention, in step S1, the orbit parameter information is the instantaneous elements of the orbit, including the semi-major axis, eccentricity, orbit inclination, right ascension of the ascending node, argument of perigee and mean anomaly of the orbit;

[0011] The scenario time is the task start time and task end time that the task planning needs to cover;

[0012] The energy constraint requirement of the whole satellite is: when the satellite performs the SAR imaging task, the maximum time of the payload being turned on continuously in a single cycle is required to be less than or equal to the maximum threshold value T of the payload being turned on continuously in a single cycle MaxPldOn The shortest time for the load to be turned on continuously in a single cycle is greater than or equal to the minimum threshold value T for the load to be turned on continuously in a single cycle MinPldOn The maximum cumulative imaging time of a single cycle with a load is less than the minimum threshold of the cumulative imaging time of a single cycle with equal load at T MaxAccImg , where T MaxAccImg <T MaxPldOn ;

[0013] The load capacity constraint requirement is the load field range Angle Fov , the interval between two imaging tasks is greater than or equal to the minimum threshold T of the interval between imaging tasks MinMissGap ;

[0014] The target task set is represented by Tar={tar1, tar2...tar i ...tar n}, n is the total number of input task targets, tar represents the information of the i-th task target, recorded as tar i ={ID,lat i ,lon i ,alt i ,dur i ,pro i}, ID, lat i ,lon i 、alt i 、dur i and pro i They are respectively represented as the number, latitude, longitude, elevation, observation time and priority of the i-th target input, i∈[1,n].

[0015] According to a technical solution of the present invention, in step S2, the visibility calculation of the imaging target in the target task set specifically includes:

[0016] Within the scope of the scene time, the input target task set is traversed in each lap to determine whether the task target in the target task set can be covered by the payload field of view in each lap, that is, whether it is visible; if visible, the visible target is associated with the corresponding lap and stored;

[0017] The results after all traversals are completed are stored as:

[0018] CircWIN={circwin1,circwin2...circwin k ...circwin m}

[0019] Where m is the total number of circles covered by the scene, circwin k Represents the result of the k-th circle traversal, denoted as circwin k ={num,Obstar1,Obstar2...Obstar j ...Obstar num}, num is the number of visible targets in the kth round, Obstar j Represents the target information of the jth visible target, denoted as

[0020] Obstar j ={ID,lat j ,lon j ,alt j ,dur j ,pro j ,nmRoll j ,nmTime j ,BgnT j ,EndT j}, which is represented by the number, latitude, longitude, altitude, observation duration, priority, nominal observation angle, nominal observation time, observation start time and observation end time of the jth visible target in the current circle, j∈[1,num].

[0021] According to a technical solution of the present invention, in step S3, the structural imaging task scheduling strategy completes the imaging target conflict resolution, specifically including:

[0022] Step S311, arranging all visible objects associated with the rounds in ascending order according to the nominal observation time;

[0023] Step S312: traverse all visible targets in a loop according to the number of rounds, and for each visible target whose task interval is less than the minimum imaging task interval time threshold T MinMissGap If BgnT j+1 -EndTj <T MinMissGap , that is, the difference between the start observation time of the next visible target and the end observation time of the previous visible target is less than the minimum threshold value T of the task interval MinMissGap , compare the priority of the two visible targets before and after j and pro j+1 , keep the visible target corresponding to the high priority, delete the visible target corresponding to the low priority, if the two have the same priority, then keep the previous visible target according to the principle of first observation first;

[0024] Step S313: output the result after completing the imaging target conflict resolution, expressed as:

[0025] CircWIN={circwin1,circwin2...circwin k ...circwin m}

[0026] Among them, m is the total number of cycles covered by the scene,

[0027] circwin k ={numMinus,Obstar1,Obstar2...Obstar j ...Obstar numMinus}, numMinus is the number of visible targets retained after the k-th round of imaging target conflict resolution, j∈[1,numMinus].

[0028] According to a technical solution of the present invention, in step S3, determining the imaging window by a rolling imaging window planning strategy specifically includes:

[0029] Step S314: cyclically process the process in turns, taking the observation start time of each visible target in each turn as the start time of the imaging window, and taking the longest continuous power-on time of the load in a single turn as the window length to form multiple rolling imaging windows, expressed as

[0030] tmpImgWIN={BgnT,EndT,DurT}

[0031] Wherein, tmpImgWIN represents the rolling imaging window information, BgnT represents the observation start time of the rolling imaging window, and BgnT=BgnT j , BgnT j Indicates the start observation time of the jth visible target, j∈[1, numMinus]; EndT indicates the end observation time of the rolling imaging window, EndT=BgnT+T MaxPldOn ; DurT represents the observation duration of the rolling imaging window, DurT=TMaxPldOn ;

[0032] Step S315: Calculate the priority sum of the visible targets in the time period of each rolling imaging window at the nominal observation time, and at the same time, each rolling imaging window needs to satisfy that the sum of the observation time of the visible targets in the rolling imaging window is less than T MaxAccImg , expressed as:

[0033]

[0034] tmpAccImgT<T MaxAccImg

[0035] Among them, tmpPro represents the total priority of the visible targets within the rolling imaging window time period, ImgNum represents the total number of visible targets within the rolling imaging window, and pro r represents the priority of the rth visible target within the rolling imaging window period, AccImgT represents the total observation time of the visible targets within the rolling imaging window, and dur r represents the observation time of the rth visible target within the rolling imaging window, T MaxAccImg Indicates the minimum threshold of the cumulative imaging time of a single load cycle;

[0036] Step S316: Calculate the total number of visible targets in each of the rolling imaging windows, expressed as:

[0037] tmpImgNum=ImgNum

[0038] Step S317, calculating the actual imaging window length of each rolling imaging window covering the visible target, expressed as:

[0039] tmpDurT=EndT ImgNum -BgnT1

[0040] Among them, tmpDurT represents the actual imaging window length of the rolling imaging window covering the visible target, EndT ImgNum BgnT1 indicates the observation end time of the last visible target covered in the rolling imaging window, and BgnT2 indicates the observation start time of the first visible target covered in the rolling imaging window;

[0041] Step S318: For each of the rounds, retain the rolling imaging window with the largest total priority as the rolling imaging window of the round, expressed as:

[0042] imgwin k =tmpImgWIN|Max(tmpPro)

[0043] Among them, imgwin krepresents the rolling imaging window retained in the kth round, tmpImgWIN represents the rolling imaging window information, tmpPro represents the total priority of visible targets within the rolling imaging window time period, and Max(·) represents the function of taking the maximum priority;

[0044] Step S319: For each of the rounds, when there are several rolling imaging windows with the largest and the same priority sum, the rolling imaging window with the larger total number of visible targets is retained as the rolling imaging window of the round, which is expressed as:

[0045] imgwin k =tmpImgWIN|Max(tmpImgNum)

[0046] Step S320: If there are several rolling imaging windows with the same and maximum priority sum and the same and maximum and maximum visible target total number in each of the rounds, the rolling imaging window with a shorter actual imaging window length covering the visible target is retained as the rolling imaging window of the round, which is expressed as:

[0047] imgwin k =tmpImgWIN|Max(tmpImgNum)

[0048] Step S321, outputting the rolling imaging window after each round of processing is completed, expressed as:

[0049] ImgWIN={Imgwin1,Imgwin2...Imgwin k ...Imgwin m}.

[0050] According to a technical solution of the present invention, in step S4, the processing of the imaging window duration is completed, and the imaging task scheduling result that meets the strong constraint of the whole star energy is output, specifically including:

[0051] Obtain the imaging windows of each round outputted in step S3

[0052] ImgWIN={Imgwin1,Imgwin2...Imgwin k ...Imgwin m The observation time DurT is less than the minimum threshold value T of the load single-cycle continuous power-on time. MinPldOn The imaging window is processed as follows:

[0053] EndT=BgnT+T MinPldOn

[0054] After processing, ImgWIN = {Imgwin1, Imgwin2...Imgwink ...Imgwin m} and the imaging targets contained in the window are the imaging task scheduling results that meet the strong energy constraints of the entire star.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention proposes a SAR imaging task planning and scheduling method based on strong satellite energy constraints. By acquiring task information, visibility calculation is performed on imaging targets in a target task set. Imaging target conflicts are resolved in combination with an imaging task scheduling strategy. The imaging window is determined by a rolling imaging window planning strategy. The imaging window duration is processed based on payload capacity constraints. The method proposed in the present invention can effectively solve the imaging task planning and scheduling problem of SAR imaging satellites under conditions of strong energy constraints. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 The flowchart of the SAR imaging task planning and scheduling method based on strong satellite energy constraints provided in one embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0059] The description of the embodiments of this specification should be combined with the corresponding drawings, which should be considered as part of the complete specification. In the drawings, the shape or thickness of the embodiments may be enlarged and indicated for simplification or convenience. Furthermore, the parts of each structure in the drawings will be described separately. It is worth noting that the elements not shown in the drawings or not described in words are in a form known to ordinary technicians in the relevant technical field.

[0060] The description of the embodiments herein and any reference to directions and orientations are only for the convenience of description and are not to be construed as any limitation on the scope of protection of the present invention. The following description of the preferred embodiments may involve combinations of features, which may exist independently or in combination, and the present invention is not particularly limited to the preferred embodiments. The scope of the present invention is defined by the claims.

[0061] like Figure 1 As shown, a SAR imaging task planning and scheduling method based on strong satellite energy constraints of the present invention includes:

[0062] Step S1, obtaining mission information, which includes orbital parameter information, scenario time, whole-satellite energy constraint requirements, payload capacity constraint requirements, and target mission set.

[0063] The orbital parameter information is the instantaneous elements of the orbit, specifically the semi-major axis, eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee, and mean anomaly of the orbit;

[0064] The scenario time is the task start time and task end time that the task planning needs to cover;

[0065] The energy constraint requirement for the entire satellite is: when the satellite performs the SAR imaging mission, the maximum continuous power-on time of the payload in a single cycle is required to be less than or equal to the maximum threshold value T of the continuous power-on time of the payload in a single cycle MaxPldOn The shortest time for the load to be turned on continuously in a single cycle is greater than or equal to the minimum threshold value T for the load to be turned on continuously in a single cycle MinPldOn , the maximum cumulative imaging time of the payload in a single cycle is less than or equal to the minimum threshold value T of the cumulative imaging time of the payload in a single cycle MaxAccImg , where T MaxAccImg <T MaxPldOn .

[0066] The load capacity constraint requirement is the load field of view range Angle Fov , the interval between two imaging tasks is greater than or equal to the minimum threshold T of the interval between imaging tasks MinMissGap .

[0067] The target task set is Tar = {tar1, tar2...tar i ...tar n}, n is the total number of task targets entered, and the task targets are expressed as tar i ={ID,lat i ,lon i ,alt i ,dur i ,pro i}, ID, lat i ,lon i 、alt i 、dur i and pro i They represent the number, latitude, longitude, altitude, observation time and priority of the i-th mission target input, i∈[1,n].

[0068] Step S2: Based on orbit parameter information, scene time, load capacity constraint requirements and target task set, visibility calculation is performed on the task targets in the target task set.

[0069] Within the scenario time range, traverse the input target task set every lap to determine whether the task target can be covered by the payload field of view in each lap. Fov , that is, whether it is visible. If it is visible, the target information of the visible task target is associated with its corresponding round and stored. The result after all traversals are completed is stored as:

[0070] CircWIN={circwin1,circwin2...circwin k ...circwin m}

[0071] Where m is the total number of circles covered by the scene, circwin k Represents the result of the k-th circle traversal, denoted as circwin k ={num,Obstar1,Obstar2...Obstar j ...Obstar num}, num is the number of visible targets in the kth round, Obstar j Represents the target information of the jth visible target, denoted as

[0072] Obstar j ={ID,lat j ,lon j ,alt j ,dur j ,pro j ,nmRoll j ,nmTime j ,BgnT j ,EndT j}, which is represented by the number, latitude, longitude, altitude, observation duration, priority, nominal observation angle, nominal observation time, observation start time and observation end time of the jth visible target in the current circle, j∈[1,num].

[0073] Step S3, imaging target conflict resolution and rolling imaging window calculation: Based on the energy constraint requirements and payload capacity constraint requirements of the entire satellite, combined with the imaging task scheduling strategy, imaging target conflict resolution is completed, and the rolling imaging window for each round is determined through the rolling imaging window planning strategy.

[0074] In step S3, imaging target conflict resolution is completed in combination with the imaging task scheduling strategy, which specifically includes:

[0075] Step S311, arranging all visible objects associated with the rounds in ascending order according to the nominal observation time;

[0076] Step S312: traverse all visible targets in a loop according to the number of rounds. For the task interval between the two visible targets before and after is less than T MinMissGap If BgnT j+1 -EndT j <T MinMissGap , that is, the difference between the start time of the next visible target and the end time of the previous observed target is less than the minimum threshold value T of the task interval MinMissGap , compare the priority of the two visible targets before and after j and pro j+1 , keep the visible target corresponding to the high priority, delete the visible target corresponding to the low priority, if the two have the same priority, then keep the previous visible target according to the principle of first observation first;

[0077] Step S313: output the result after completing the imaging target conflict resolution, expressed as:

[0078] CircWIN={circwin1,circwin2...circwin k ...circwin m}

[0079] Among them, m is the total number of cycles covered by the scene,

[0080] circwin k ={numMinus,Obstar1,Obstar2...Obstar j ...Obstar numMinus}, numMinus is the number of visible targets retained after the k-th round of imaging target conflict resolution, j∈[1,numMinus].

[0081] In step S3, the imaging window is determined by a rolling imaging window planning strategy, which specifically includes:

[0082] Step S314: Process in a cyclic manner, taking the observation start time of each visible target in each lap as the start time of the imaging window, and taking the maximum threshold value T of the continuous power-on time of the load in a single lap as the start time of the imaging window. MaxPldOn As the window length, multiple rolling imaging windows are formed, which is expressed as:

[0083] tmpImgWIN={BgnT,EndT,DurT}

[0084] Wherein, tmpImgWIN represents the rolling imaging window information; BgnT represents the observation start time of the rolling imaging window, BgnT=BgnT j , BgnT jIndicates the start observation time of the jth visible target, j∈[1, numMinus]; EndT indicates the end observation time of the rolling imaging window, EndT=BgnT+T MaxPldOn ; DurT represents the observation duration of the rolling imaging window, DurT=T MaxPldOn ;

[0085] The number of the formed rolling imaging windows is the same as the number of visible objects in the circle, and the formed multiple rolling imaging windows correspond one-to-one to the visible objects in the circle.

[0086] Step S315: Calculate the priority sum of the visible targets in each rolling imaging window, and at the same time, each rolling imaging window satisfies that the sum of the observation time of the visible targets in the rolling imaging window is less than the minimum threshold value T of the payload single-circle cumulative imaging time. MaxAccImg , expressed as:

[0087]

[0088] tmpAccImgT<T MaxAccImg

[0089] Among them, tmpPro represents the total priority of the visible targets within the rolling imaging window time period, ImgNum represents the total number of visible targets within the rolling imaging window, and pro r represents the priority of the rth visible target within the rolling imaging window period, AccImgT represents the total observation time of the visible targets within the rolling imaging window, and dur r represents the observation time of the rth visible target within the rolling imaging window, T MaxAccImg Indicates the minimum threshold of the cumulative imaging time of a single load cycle;

[0090] Step S316: Calculate the total number of visible targets in each rolling imaging window, expressed as:

[0091] tmpImgNum=ImgNum

[0092] Step S317: Calculate the actual imaging window length of each rolling imaging window covering the visible target, expressed as:

[0093] tmpDurT=EndT ImgNum -BgnT1

[0094] Among them, tmpDurT represents the actual imaging window length of the rolling imaging window covering the visible target, EndT ImgNum BgnT1 indicates the observation end time of the last visible target covered in the rolling imaging window, and BgnT2 indicates the observation start time of the first visible target covered in the rolling imaging window;

[0095] Step S318: For each round, retain the rolling imaging window with the largest total priority as the rolling imaging window of the round, expressed as:

[0096] imgwin k =tmpImgWIN|Max(tmpPro)

[0097] Among them, imgwin k represents the rolling imaging window retained in the kth round, tmpImgWIN represents the rolling imaging window information, tmpPro represents the total priority of visible targets within the rolling imaging window time period, and Max(·) represents the function of taking the maximum priority;

[0098] Step S319: For each round, if there are several rolling imaging windows with the largest and the same priority sum, the rolling imaging window with the larger total number of visible targets is retained as the rolling imaging window of the round, which is expressed as:

[0099] imgwin k =tmpImgWIN|Max(tmpImgNum)

[0100] Step S320: If there are several rolling imaging windows with the same maximum and maximum total priority and the same total number of visible targets in each round, the rolling imaging window with a shorter actual imaging window length covering the visible targets is retained as the rolling imaging window of the round, which is expressed as:

[0101] imgwin k =tmpImgWIN|Min(tmpDurT)

[0102] Step S321, output the rolling imaging window after each round of processing, expressed as:

[0103] ImgWIN={Imgwin1,Imgwin2...Imgwin k ...Imgwin m}.

[0104] Step S4: Complete the duration processing of the imaging window based on the load capacity constraint requirement, and output the imaging task scheduling result that meets the energy constraint requirement of the entire satellite.

[0105] For each output imaging window ImgWIN = {Imgwin1, Imgwin2...Imgwin k ...Imgwin m The observation time DurT is less than the minimum threshold value T of the load single-cycle continuous power-on time. MinPldOn The imaging window is processed as follows:

[0106] EndT=BgnT+T MinPldOn

[0107] After processing, ImgWIN = {Imgwin1, Imgwin2...Imgwin k ...Imgwin m} and the imaging targets contained in the window are the imaging task scheduling results that meet the strong energy constraints of the entire star.

[0108] It should be noted that the above is a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, once the basic creative concept of the present invention is known, a number of improvements and modifications can be made by a person skilled in the art without departing from the principles of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A SAR imaging mission planning and scheduling method based on strong satellite energy constraints, characterized in that: The following steps are involved: Step S1, obtaining mission information, wherein the mission information includes orbit parameter information, scenario time, whole-satellite energy constraint requirements, payload capacity constraint requirements and target mission set; Step S2, based on the orbit parameter information, the scene time, the load capacity constraint requirement and the target task set, performing visibility calculation on the imaging target in the target task set; Step S3: Based on the energy constraint requirements of the entire satellite and the load capacity constraint requirements, combined with the imaging task scheduling strategy, complete the imaging target conflict resolution, and determine the rolling imaging window of each round through the rolling imaging window planning strategy; Step S4: completing the duration processing of the imaging window based on the load capacity constraint requirement, and outputting the imaging task scheduling result that meets the energy constraint requirement of the entire satellite.

2. The SAR imaging mission planning and scheduling method based on strong satellite energy constraints according to claim 1 is characterized in that: In step S1, the orbit parameter information is the instantaneous elements of the orbit, including the semi-major axis, eccentricity, orbit inclination, right ascension of the ascending node, argument of perigee and mean anomaly of the orbit; The scenario time is the task start time and task end time that the task planning needs to cover; The energy constraint requirement of the whole satellite is: when the satellite performs the SAR imaging task, the maximum time of the payload being turned on continuously in a single cycle is required to be less than or equal to the maximum threshold value T of the payload being turned on continuously in a single cycle MaxPldOn The shortest time for the load to be turned on continuously in a single cycle is greater than or equal to the minimum threshold value T for the load to be turned on continuously in a single cycle MinPldOn The maximum cumulative imaging time of a single cycle with a load is less than the minimum threshold of the cumulative imaging time of a single cycle with equal load at T MaxAccImg , where T MaxAccImg <T MaxPldOn ; The load capacity constraint requirement is the load field of view range Angle Fov , the interval between two imaging tasks is greater than or equal to the minimum threshold T of the interval between imaging tasks MinMissGap ; The target task set is represented by Tar={tar1, tar2...tar i ...tar n }, n is the total number of input task targets, tar represents the information of the i-th task target, recorded as tar i ={ID,lat i ,lon i ,alt i ,dur i ,pro i }, ID, lat i ,lon i 、alt i 、dur i and pro i They are respectively represented as the number, latitude, longitude, elevation, observation time and priority of the i-th target input, i∈[1,n].

3. The SAR imaging mission planning and scheduling method based on strong satellite energy constraints according to claim 1 is characterized in that: In the step S2, the visibility calculation of the imaging target in the target task set specifically includes: Within the scope of the scene time, the input target task set is traversed in each lap to determine whether the task target in the target task set can be covered by the payload field of view in each lap, that is, whether it is visible; if visible, the visible target is associated with the corresponding lap and stored; The results after all traversals are completed are stored as: CircWIN={circwin1,circwin2…circwin k …circwin m } Where m is the total number of circles covered by the scene, circwin k Represents the result of the k-th circle traversal, denoted as circwin k ={num,Obstar1,Obstar2…Obstar j …Obstar num }, num is the number of visible targets in the kth round, Obstar j Represents the target information of the jth visible target, denoted as Obstar j ={ID,lat j ,lon j ,alt j ,dur j ,pro j ,nmRoll j ,nmTime j ,BgnT j ,EndT j }, which is represented by the number, latitude, longitude, altitude, observation duration, priority, nominal observation angle, nominal observation time, observation start time and observation end time of the jth visible target in the current circle, j∈[1,num].

4. The SAR imaging mission planning and scheduling method based on strong satellite energy constraints according to claim 1 is characterized in that: In step S3, the structural imaging task scheduling strategy completes the imaging target conflict resolution, specifically including: Step S311, arranging all visible objects associated with the rounds in ascending order according to the nominal observation time; Step S312: traverse all visible targets in a loop according to the number of rounds, and for each visible target whose task interval is less than the minimum imaging task interval time threshold T MinMissGap If BgnT j+1 -EndT j <T MinMissGap , that is, the difference between the start observation time of the next visible target and the end observation time of the previous visible target is less than the minimum threshold value T of the task interval MinMissGap , compare the priority of the two visible targets before and after j and pro j+1 , keep the visible target corresponding to the high priority, delete the visible target corresponding to the low priority, if the two have the same priority, then keep the previous visible target according to the principle of first observation first; Step S313: output the result after completing the imaging target conflict resolution, expressed as: CircWIN={circwin1,circwin2...circwin k ...circwin m } Among them, m is the total number of cycles covered by the scene, circwin k ={numMinus,Obstar1,Obstar2...Obstar j ...Obstar numMinus }, numMinus is the number of visible targets retained after the k-th round of imaging target conflict resolution, j∈[1,numMinus].

5. The SAR imaging mission planning and scheduling method based on strong satellite energy constraints according to claim 4 is characterized in that: In step S3, determining the imaging window by a rolling imaging window planning strategy specifically includes: Step S314: cyclically process the process in turns, taking the observation start time of each visible target in each turn as the start time of the imaging window, and taking the longest continuous power-on time of the load in a single turn as the window length to form multiple rolling imaging windows, expressed as tmpImgWIN={BgnT,EndT,DurT} Wherein, tmpImgWIN represents the rolling imaging window information, BgnT represents the observation start time of the rolling imaging window, and BgnT=BgnT j , BgnT j Indicates the start observation time of the jth visible target, j∈[1, numMinus]; EndT indicates the end observation time of the rolling imaging window, EndT=BgnT+T MaxPldOn ; DurT represents the observation duration of the rolling imaging window, DurT=T MaxPldOn ; Step S315: Calculate the priority sum of the visible targets within each rolling imaging window time period, and at the same time, each rolling imaging window needs to satisfy that the total observation time of the visible targets within the rolling imaging window is less than T MaxAccImg , expressed as: tmpAccImgT<T MaxAccImg Among them, tmpPro represents the total priority of the visible targets within the rolling imaging window time period, ImgNum represents the total number of visible targets within the rolling imaging window, and pro r represents the priority of the rth visible target within the rolling imaging window period, AccImgT represents the total observation time of the visible targets within the rolling imaging window, and dur r represents the observation time of the rth visible target within the rolling imaging window, T MaxAccImg Indicates the minimum threshold of the cumulative imaging time of a single load cycle; Step S316: Calculate the total number of visible targets in each of the rolling imaging windows, expressed as: tmpImgNum=ImgNum Step S317, calculating the actual imaging window length of each rolling imaging window covering the visible target, expressed as: tmpDurT=EndT ImgNum -BgnT1 Among them, tmpDurT represents the actual imaging window length of the rolling imaging window covering the visible target, EndT ImgNum BgnT1 indicates the observation end time of the last visible target covered in the rolling imaging window, and BgnT2 indicates the observation start time of the first visible target covered in the rolling imaging window; Step S318: For each of the rounds, retain the rolling imaging window with the largest total priority as the rolling imaging window of the round, expressed as: imgwin k =tmpImgWIN|Max(tmpPro) Among them, imgwin k represents the rolling imaging window retained in the kth round, tmpImgWIN represents the rolling imaging window information, tmpPro represents the total priority of visible targets within the rolling imaging window time period, and Max(·) represents the function of taking the maximum priority; Step S319: For each of the rounds, when there are several rolling imaging windows with the largest and the same priority sum, the rolling imaging window with the larger total number of visible targets is retained as the rolling imaging window of the round, which is expressed as: imgwin k =tmpImgWIN|Max(tmpImgNum) Step S320: If there are several rolling imaging windows with the same and maximum priority sum and the same and maximum and maximum visible target total number in each of the rounds, the rolling imaging window with a shorter actual imaging window length covering the visible target is retained as the rolling imaging window of the round, which is expressed as: imgwin k =tmpImgWIN|Max(tmpImgNum) Step S321, outputting the rolling imaging window after each round of processing, expressed as: ImgWIN={Imgwin1,Imgwin2...Imgwin k ...Imgwin m }。 6. The SAR imaging mission planning and scheduling method based on strong satellite energy constraints according to claim 5 is characterized in that: In step S4, the processing of the imaging window duration is completed, and the imaging task scheduling result satisfying the strong constraint of the whole star energy is output, which specifically includes: Obtain the imaging windows of each circle outputted in step S3 ImgWIN={Imgwin1,Imgwin2...Imgwin k ...Imgwin m The observation duration DurT is less than the minimum threshold value T of the load single-cycle continuous power-on duration. MinPldOn The imaging window is processed as follows: EndT=BgnT+T MinPldOn After processing, ImgWIN = {Imgwin1, Imgwin2...Imgwin k ...Imgwin m } and the imaging targets contained in the window are the imaging task scheduling results that meet the strong energy constraints of the entire star.

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