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    • 专利摘要:
    The invention relates to a method for planning the acquisition of images of terrestrial zones Z1,..., ZN, by a spacecraft in mission around the Earth, each terrestrial zone Zi being associated with a request Ri so that said zone Zi corresponds to a temporal interval of visual accessibility Ti. In addition, the method comprises the steps of: - determining for each interval Ti discrete acquisition opportunities Zi zone so that each discrete acquisition opportunity associated with a start date, a duration of execution, a kinematic local constraint and a weight, - grouping discrete acquisition opportunities Zi zones in a set D, - ranking discrete acquisition opportunities Di of the set D by increasing start date, - evaluation kinematic compatibility between said discrete acquisition opportunities of the set D, - determining an optimum sequence of discrete acquisition opportunities having a maximum weight, and kinematically compatible.
    公开号:FR3039728A1
    申请号:FR1557215
    申请日:2015-07-28
    公开日:2017-02-03
    发明作者:Pierre Blanc-Paques
    申请人:Airbus Defence and Space SAS；
    IPC主号:
    专利说明:

    TECHNICAL AREA
    The present invention belongs to the field of terrestrial imagery by spacecraft, such as observation satellites, and more particularly relates to a method of planning the acquisition of images of terrestrial areas by a spacecraft or a constellation of such spacecraft. The invention finds a particularly advantageous application, although in no way limiting, in the case of observation satellites operating in a strip image acquisition mode, a mode subsequently designated in the text by the term "comb" known of the man of the art (still called "pushbroom" mode in reference to the Anglo-Saxon literature).
    STATE OF THE ART
    Earth observation missions carried out by a spacecraft consist in acquiring images of terrestrial areas, that is to say located on the surface of the Earth, in response to requests from customers. In particular, such a spacecraft follows a moving orbit around the Earth so as to be able to acquire said terrestrial areas when flying over them for a predetermined duration. In addition, the development of the agility of such a spacecraft makes it possible to increase the number of imagined terrestrial zones, the latter can now be located on either side of the said orbit or acquired from different angles during several orbits. Thus, at any moment along said scrolling orbit corresponds one or more opportunities for acquiring images of different terrestrial areas.
    The receipt of said requests by the spacecraft is done regularly, usually on a daily basis. Currently, requests for such acquisitions of terrestrial areas are increasing in number, as they are no longer limited solely to industrial sectors historically linked to the space imaging sector. For example, and without limitation, the agriculture sector is now making significant use of terrestrial observations in order to optimize the exploitation of agrarian surfaces. Consequently, the number of requests to be processed by such a spacecraft continues to increase, which is also the case of their complexity insofar as these requests include specific constraints associated with the terrestrial area to be acquired, such as for example location conditions, light exposure, or the need for multiple acquisitions in order to obtain stereo, tri-stereo or multiband images. Added to this is the fact that requests are differentiable according to their priority level.
    The management of the constraints associated with said requests must also be considered in parallel with the management of operating constraints associated with said spacecraft, whether of the cumulative type (memory size, electrical power consumed, maximum operating time of embedded instruments). , or even of local type (minimum duration between two successive acquisitions).
    It is thus clear that the objective of satisfying a set of such requests is a very strongly constrained problem necessitating the planning in time, according to the orbit of said spacecraft, of the shots to be made. More broadly, such a problem falls within the class of "commercial traveler" optimization problems, well known to be very difficult to solve in a reasonable time.
    The problem is particularly critical in the case where the user's request has to be satisfied within a short time. The increase in the number of satellites gives the possibility of having satellite access to an area in much shorter time. However, this capacity can only be fully used if the update of the acquisition plan can also be done in a short time. If it is nevertheless known that such a planning problem admits good-quality approximation solutions thanks to optimization heuristic techniques (for example of the greedy type), their calculation times do not bring satisfaction with regard to the volume of requests to be processed under operational conditions.
    More recently, resolution techniques based on significant simplification hypotheses, notably concerning a decoupled management of the local and cumulative constraints of this machine, have made it possible to provide solutions in a reasonable time to the management of said local constraints, which is a first step before the overall resolution of said planning problem. While some of these techniques do indeed make it possible to take into account the cumulative constraints, none of them makes it possible however to take into account the acquisition of stereo, tri-stereo or multiband images, in particular in the case of a satellite d observation operating in comb mode. Therefore, these techniques are limiting and not optimal as to the number of requests that they can satisfy.
    STATEMENT OF THE INVENTION
    The present invention aims to remedy all or part of the disadvantages of the prior art, including those described above, by proposing a solution that allows for an optimal planning process for the satisfaction of local and cumulative constraints of a spacecraft and which allows to take into account land areas requiring to be acquired a plurality of times or even once, For this purpose, the invention relates to a method of planning acquisition of images of terrestrial areas Ζι,.,., Ζν, by a spacecraft in mission around the Earth following a predetermined scrolling orbit, such as for example an observation satellite, each terrestrial zone Zi being associated with a request Rj so that said zone Zi corresponds to a temporal interval of visual accessibility Ti along said moving orbit, 1 <is N, In addition, said method comprises the successive steps following: - a determination step for each interval T, discrete acquisition opportunities of the zone Zi so that each discrete acquisition opportunity associated with a start date included in said interval T "a duration d execution, a kinematic local constraint as well as a weight, - a step of grouping the discrete acquisition opportunities of the zones Z, in a set D, - a step of classification of the discrete acquisition opportunities of the set D, the acquisition opportunities being classified by increasing start date and denoted by D '; a step of evaluation of kinematic compatibility between said discrete acquisition opportunities of the set D, taken two by two according to their respective rankings; step of determining an optimal sequence of discrete acquisition opportunities having a maximum weight, and kinematically compatible.
    In particular modes of implementation, the terrestrial image acquisition planning method comprises one or more of the following characteristics, taken separately or in any technically possible combination.
    In a particular mode of implementation, the method comprises a step of taking into account multiple acquisition requests, subsequent to the kinematic compatibility evaluation step and prior to the step of determining an optimal sequence, wherein the respective weights of discrete acquisition opportunities associated with Z zones to be acquired a plurality of times are updated and wherein a mustHit variable forces the concatenation of said discrete acquisition opportunities to satisfy said queries. multiple acquisitions.
    In a particular mode of implementation, the step of determining an optimal sequence comprises dynamically updating a pathMesh variable storing the Z zones, associated with the discrete acquisition opportunities of said sequence, so as to prevent the duplication of discrete acquisition opportunities for areas to be acquired once.
    In a particular mode of implementation, the step of determining an optimal sequence comprises for each discrete acquisition opportunity D1 of the set D a partial selection of discrete acquisition opportunities preceding D1 in D, and compatible kinematically with D1, among all the discrete acquisition opportunities preceding D1 in D, and kinematically compatible with D1.
    In a particular mode of implementation, the method comprises a step of checking compliance with at least one cumulative constraint imposed on said spacecraft, said verification step being consecutive to the step of determining an optimal sequence.
    In a particular mode of implementation, said at least one cumulative constraint comprises a memory size constraint.
    In a particular mode of implementation, said at least one cumulative constraint comprises a consumed electric power constraint.
    In a particular mode of implementation, said at least one cumulative constraint comprises a maximum time constraint of operation of instruments embedded in said machine.
    In a particular mode of implementation, the step of checking compliance with cumulative constraints comprises a dynamic update of said optimal sequence by eliminating discrete acquisition opportunities, as long as said cumulative constraints are not met.
    In a particular mode of implementation, the start dates of the discrete acquisition opportunities of each interval T, are sampled temporally according to a constant time step.
    In a particular mode of implementation, the respective time steps of the intervals Ti, ..., Tn are equal to each other.
    In a particular mode of implementation, the respective time steps of at least two intervals Tj and Tj are different.
    In a particular mode of implementation, the time step of each interval T is adjusted so that said interval T is associated with 20 discrete acquisition opportunities.
    In a particular mode of implementation, the kinematic local stress of a discrete acquisition opportunity comprises an attitude setpoint of said spacecraft at the beginning and at the end of said discrete acquisition opportunity.
    In a particular mode of implementation, the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority of the request R, associated with said zone Z,.
    In a particular mode of implementation, each Z zone is associated with a quality criterion w, depending on the geometric characteristics of said Z zone, as well as the meteorological conditions provided during the visual accessibility time interval Ti.
    In a particular mode of implementation, the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority of the request R, so as to be a vector whose only non-zero component is equal to the quality criterion w ,, the position of said non-zero component in said vector depending on the priority of said request R ,.
    In a particular mode of implementation, said non-zero component depends on the quality criterion w, and a criterion of acquisition interest associated with said discrete acquisition opportunity.
    In a particular mode of implementation, the step of determining an optimal sequence comprises a comparison of the respective weights of the discrete acquisition opportunities kinematically compatible with each other.
    In a particular mode of implementation, the method comprises a step of aggregation of terrestrial areas, prior to the step of determining discrete acquisition opportunities.
    In a particular mode of implementation, said spacecraft is an observation satellite operating in comb mode.
    PRESENTATION OF FIGURES
    The characteristics and advantages of the invention will be better appreciated thanks to the description which follows, a description which sets out the characteristics of the invention through preferred embodiments, which are in no way limiting thereto.
    The description is based on the appended figures which represent: FIG. 1: a representation of a flowchart of an exemplary implementation of a planning method for acquiring images of terrestrial areas. , Ζν by a spacecraft. - Figure 2: a representation of a preferred mode of implementation of the method of Figure 1 in which the method comprises a verification step of compliance with at least one cumulative stress imposed on said spacecraft. - Figure 3: a representation of a particular embodiment of the method of Figure 1 in which the method comprises a step of aggregating terrestrial areas. - Figure 4: a representation of a preferred mode of implementation of the method of Figure 1 in which are taken into account the terrestrial areas to be acquired a single time or a plurality of times.
    DETAILED DESCRIPTION OF A PE MODE REALIZING
    THE INVENTION
    The present invention belongs to the field of planning acquisition of images of terrestrial areas by a spacecraft mission around the Earth following a predetermined scrolling orbit.
    FIG. 1 represents a flowchart of an exemplary implementation of a planning method for acquiring terrestrial image images Z1,..., ZN by a spacecraft.
    By "image acquisition" is meant here the measurement of electromagnetic radiation received from said terrestrial zones Zi, ..., ZN. For this purpose, the spatial Pengin includes an optical device for performing a plurality of image acquisitions, said optics further comprising sensors adapted to measure said electromagnetic radiation. Said images are finally converted to digital format and stored within a limited capacity memory embedded by said spacecraft.
    The remainder of the description is directed more specifically, but in a non-limiting manner, to a method for planning the acquisition of images of terrestrial areas by an agile observation satellite in moving orbit (LEO or MEO, acronyms of the respective English expressions "Low"). Earth Orbit "and" Medium Earth Orbit "). For example, said agile observation satellite follows a quasi-polar heliosynchronous orbit at constant altitude. It comprises an instrument adapted to acquire images in comb mode in successive bands according to different directions of acquisition.
    However, according to other non-detailed examples, nothing excludes the consideration of other types of spacecraft (space shuttle, spacecraft, etc.) adapted to acquiring images of terrestrial areas, as well as other types of spacecraft. instruments or other modes of image acquisition, for example with "step and stare" mode matrix detectors.
    The terrestrial areas Z 1,..., Z n are ground surfaces, finite respective areas, possibly contiguous and intersect the swath of said observation satellite. The agility of the satellite authorizes the acquired terrestrial areas to be positioned on the one hand, along the projection of said moving orbit on the earth's surface, and on the other hand of this projection on the earth's surface. .
    In the following description, each terrestrial zone Z is associated with a request R, issued by a user. Each request Ri can itself be associated with different parameters: a priority p ,, ps being for example a natural integer, which characterizes the need to satisfy this request Rj before possibly other requests. Each priority pi depends on several factors such as the importance and cost of the request R, on which it depends, acquisition constraints depending on several factors, such as the attitude of the satellite (which determines the orientation the aiming direction), or the meteorological conditions necessary for an acquisition of good quality and which must be satisfied at the times when the satellite is potentially able to acquire the Z-zone, associated with the said request Ri, - a type acquisition (mono, stereo, tri-stereo). Indeed, certain zones Zi need to be acquired a plurality of times, possibly according to a different acquisition angle, as for example in the case of stereo or tri-stereo,
    It should be noted that in general, that is to say at the moment when a request Ri is indicated by a user, the zone Zi associated with said request Rj is of any form. Therefore, and for the purpose of optimization of operation, an image acquisition campaign by the satellite is generally preceded by a formatting step of cutting said zone Z into adapted elementary zones. to be acquired by said satellite. For example, in the case of shooting in comb mode, said zones Zi are cut into a band of width less than or equal to that of the swath of the satellite.
    For the remainder of the description, it is considered that the zones Z associated with the requests Rt are of respective shapes adapted to be acquired by the optics of said satellite. In other words, said shaping step is either unnecessary with respect to the respective initial shapes of said zones Z, or considered to have been previously performed.
    Moreover, each terrestrial zone Z corresponds to a temporal interval of visual accessibility T, along said moving orbit. Said interval T, comprises a start date and an end date, and corresponds to a time duration during which the satellite can acquire an image of the zone Z, while respecting the acquisition constraints as well as the type of acquisition of the request R, which is associated with said zone Z ,.
    For the rest of the description, we also adopt the convention that the components of a vector are read from left to right by being indexed starting from 1. Thus a vector V with N components is denoted by V = (V1, V2 , ..., VN). In the same way, an element positioned on the i-th row and j-th column of a matrix M is denoted Ml, j.
    The image acquisition planning method comprises several successive steps. In its general principle, said method consists in firstly determining acquisition sequences comprising points along the satellite's traveling orbit, so that by acquiring images at the respective points of said sequences, the largest number of user queries are satisfied. Next, said method aims to determine among said acquisition sequences that satisfying an optimality criterion defined below as well as constraints inherent to the operation of said satellite. For this purpose, the method comprises firstly a step 100 for determining, for each interval T ,, discrete acquisition opportunities a}, a ·, ... of the zone Z, so that for each said discrete acquisition opportunity is associated with a start date included in said interval T ,, a running time, a kinematic local stress and a weight.
    A discrete acquisition opportunity is a point along said moving orbit which designates the possibility for the satellite to acquire an image of a zone Z ,, from a start date as well as for a period of time. execution in the interval T, of said zone Z ,, so that the acquisition constraints and the type of acquisition of the request R, associated with this zone Z, are respected.
    In the remainder of the description, an acquisition sequence designates a series of discrete acquisition opportunities.
    An interval T, comprises one or more discrete acquisition opportunities that discretize the latter according to their respective start dates. Indeed, the agility of the satellite allows the fact that a zone Z can be acquired potentially at times distinct from its interval T ,.
    In a particular mode of implementation of step 100, the start dates of the discrete acquisition opportunities of each interval T are sampled temporally according to a constant time step. It should be noted that the smaller said constant time step is chosen, the more acquisition opportunities there are within each interval T ,, thus increasing the number of possible acquisition sequences. In return, a small time step increases the computation complexity of the process.
    In a particular mode of implementation of step 100, the respective time steps of at least two intervals T 1 and T 1 are different. Such a configuration is advantageous when for example the respective priorities of the requests R, and Rj associated with said intervals T, and Tj are different. Indeed, one way of satisfying a high priority request is to associate said request with a large number of discrete acquisition opportunities so as to increase the number of points along the orbit in which the satellite makes acquisitions. the zone associated with said request, In other words, the higher the priority of a request, the more advantageous it is to finely discretize the accessibility interval associated with the latter by means of a small time step in order to have a large number of discrete acquisition opportunities within said accessibility range.
    In a particular embodiment of step 100, the respective time steps of the intervals Ti, ..., Tn are equal to each other. In this way, a single time step is chosen, which is advantageous in terms of calculation time when the respective priorities of the requests Ri,..., Rn associated with the intervals Ti,..., Tn are all identical.
    In a particular embodiment of step 100, the time step of each interval T is adjusted so that said interval T is associated with a predefined number of discrete acquisitions. For example, a number of discrete acquisitions equal to 20 is advantageous insofar as practice shows that it is a good compromise between the optimization of the process from the point of view of the calculation time and the possibility of build enough acquisition sequences to best satisfy a large number of requests.
    Furthermore, the execution time corresponds to the time required for the satellite optics to perform the acquisition under the assumption that the attitude of said satellite allows it from said acquisition start date. Thus, the duration of execution of a discrete acquisition opportunity does not include the time required to change the attitude of the satellite so that the optics of the latter is configured to make the acquisition or a possible other subsequent acquisition. By way of non-limiting example, and corresponding to the most used configurations, the execution time of an acquisition opportunity is between 5 seconds and 15 seconds.
    The kinematic local constraint of a discrete acquisition opportunity corresponds to the configuration in which the satellite must be located, and thus the orientation of the axis of aim of the instrument, at the beginning and at the end of an opportunity. discrete acquisition method to satisfy the request associated with said discrete acquisition opportunity.
    For example, the kinematic local stress of a discrete acquisition opportunity comprises an attitude setpoint of said spacecraft at the beginning and at the end of said discrete acquisition opportunity. By attitude instruction, here is meant the orientation of the satellite during an acquisition in order to satisfy the request associated with said acquisition.
    The c a { weight of a discrete acquisition opportunity has {corresponds to a general measure of the interest of acquiring a terrestrial area in the discrete acquisition opportunity with regard to all the requests received by the satellite.
    For example, the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority p, the request R, associated with said zone Z ,, so that the higher said priority, the more the respective weights of said Discrete acquisition opportunities are important.
    The weight of a discrete acquisition opportunity is also advantageously of characteristics of the terrestrial area to which said opportunity is associated. Thus, in a particular mode of implementation of step 100, each Z zone is associated with a quality criterion w [Z,] depending on the geometrical characteristics of said zone Z, as well as on the meteorological conditions predicted over the course of time. time interval of visual accessibility Ti. Said quality criterion w [Z,] is a scalar quantity characterizing, for example, the fact that zone Zi is of restricted size and therefore easier to acquire than a larger zone, but also that the meteorological conditions encountered during the time interval of visual accessibility T, associated with Z, are substantially identical to those required by the acquisition constraints of the request connected to said interval T ,.
    In a particular embodiment of step 100, the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority p, of the request R, so as to be a vector whose only component non-zero is equal to said quality criterion w [Zi], the position of said non-zero component in said vector being the priority p, of said request R ,. In this mode of implementation, the size of said vector is equal to the number of distinct priorities used to classify the requests received by the satellite during a mission. Moreover, we adopt the convention that a priority p is of greater importance than another priority Pj if and only if p, <Pj. For example, a discrete acquisition opportunity has {of a zone Z, having a quality criterion w [Zi], and is associated with a request R, of priority p, equal to 2, among a set of requests whose priorities from 1 to 4, has the weight c [a ( = (c1 [a /], c2 [a {], c3 [a {], c4 [a /]) = (0, wfZj, 0, 0) .
    Such a representation of the respective weights of the discrete acquisition opportunities is advantageous since it makes it possible to compare the weights between them by means of a natural order relation noted> operating in the following way: we note c [a]> c [b] in the sense that the weight of a discrete acquisition opportunity a is greater than the weight of a discrete acquisition opportunity b if and only if {^ [a]> c1 [ô]} V {(c ^ a] = c1 ^]) A (c2 [a]> c2 [b])} V ..., the operators λ and v respectively representing the Boolean operators "and >> and" or >>, and the operator> being the classic comparison operator between scalars. We note that the relation of order> operates by comparing component vectors by component, and is thus a lexicographic order.
    Such a representation is also advantageous because it makes it possible to define in a natural way the weight of an acquisition sequence comprising a plurality of discrete acquisition opportunities such as the sum of the weights of said discrete acquisition opportunities, the vector summation being done component by component.
    In a particular mode of implementation of step 100, said non-zero component of the weight of a discrete acquisition opportunity a {depends on the quality criterion w [Z,] as well as a criterion of interest of acquisition w [a {] associated with said discrete acquisition opportunity a {. Said acquisition interest criterion w [a {] is a scalar that measures the interest of acquiring more particularly the opportunity at {rather than another opportunity also associated with the same zone Z ,. For example, and in no way limiting, the criterion of acquisition interest depends on the acquisition angle of each opportunity of the same area Z . In addition, in this embodiment, the weight of a discrete acquisition opportunity is updated so that by taking the example above: c [a { = (0, w [Zi ] + w [a (], 0, 0).
    Such a procedure is advantageous insofar as the weight of a discrete acquisition opportunity takes into account both the characteristics of the area and the request which is associated with the discrete acquisition opportunity, but also the differences. between discrete acquisition opportunities in the same area. Thus, the weight c a { exhaustively measures the interest and the variability existing between each opportunity of discrete acquisition.
    The method then comprises a step 200 of grouping discrete acquisition opportunities of the different zones Z, in a set D.
    Each element of the set D is a discrete acquisition opportunity with associated start date, execution time, kinematic local stress and weight. Set D, as described in this step 200, thus brings together all the opportunities that may be part of one or more acquisition sequences in order to satisfy a maximum number of requests.
    The method then comprises a step 300 of ranking the discrete acquisition opportunities of the set D by increasing start date.
    Said step 300 therefore consists in ordering the elements of the set D. It is possible to classify the elements of D according to other characteristics of the discrete acquisition opportunities. For example, the latter can be classified by increasing weight (in the sense of the order relation>), by increasing execution times or even according to the queries to which they are associated. However, in the present mode of implementation, the choice has advantageously focused on a classification by increasing start date for reasons explained below.
    It should be noted that any subset of the set D thus sorted constitutes a potential acquisition sequence, that is to say a series of discrete acquisition opportunities respecting the chronology of the movement of the satellite along its length. scrolling orbit. Nevertheless, it should be ensured that the satellite can effectively realize, one after the other, the opportunities for discrete acquisitions of said potential acquisition sequence. For this purpose, the method then comprises a kinematic compatibility evaluation step 400 between said discrete acquisition opportunities of the set D, taken in pairs according to their respective rankings.
    For kinematic compatibility, here we mean that two discrete acquisition opportunities D1 and Dj of the set D, such that said opportunity D1 has a start date prior to the start date of said opportunity Dj (so such that i <j ), are chained by the satellite along its orbit. This is theoretically possible when the maneuvering time necessary for the satellite to go from the opportunity D1 to the opportunity Dj is less than the duration separating the end date of the opportunity D1 from the start date of the opportunity. Dj.
    By extension, an acquisition sequence A which is a subset of the set D is said to be kinematically compatible when its elements are two by two kinematically compatible, that is to say when Aj is kinematically compatible with Al + 1.
    Classically, the elements of the set D can be seen as the vertices of a graph G, these vertices being connected to each other by means of stops when they are kinematically compatible with one another. The structure of the set D, obtained at the end of step 300, advantageously conditions the structure of the graph G insofar as: the classification of the elements of D by increasing start date provides a natural orientation to the edges of the graph of G in the direction of increasing times: the graph G is therefore oriented, - an opportunity D 'is not kinematically compatible with a discrete acquisition opportunity Dj whose start date is earlier than that of said opportunity D' (so such as i> j). That is to say that the elements of any kinematically compatible acquisition sequence are two by two distinct. This guarantees the impossibility of the satellite to pass twice at the same place along its orbit: the graph G is therefore also acyclic. Therefore, it is understood that seeking to plan the acquisition of images of terrestrial areas is to seek kinematically compatible acquisition sequences within said graph G. More particularly, in order to satisfy as many queries as possible this amounts to looking for a kinematically compatible acquisition sequence having the highest weight in the graph G. This is an optimization problem, also known as the "search problem of the longer way >> ("longest path problem").
    The fact that the graph G is an acyclic oriented graph is advantageous insofar as it is known that in this case said optimization problem is of polynomial complexity in number of vertices of the graph G, whereas it is of exponential complexity for any graph.
    In the present embodiment, the graph G is represented by means of a square matrix M of Booleans, called adjacency matrix, whose term located at the line i and the column j is: - Ml, j = 1 if D 'and Dj are kinematically compatible, - Ml, j = 0 otherwise.
    Compatibility conditions between two discrete acquisition opportunities imply that M is a strict upper triangular matrix.
    It should be noted that the implementation of steps 100 to 400 is preferably performed on the ground, and upstream of the satellite observation mission, that is to say, possibly a long time before solving the optimization problem. . Such an implementation is advantageous insofar as the tasks performed during steps 100 to 400, and more particularly that of determining the discrete acquisition opportunities of step 100 as well as that of determining the graph G during Step 400, are easily executable by computer means according to a parallel programming scheme, thus saving time. In addition, a first implementation of steps 100 to 400 advantageously makes it possible to dispense with a new complete determination of the graph G when it is desired, for example, to include on the fly in the mission plan of the satellite an additional request, the graph G is indeed quickly and easily updated. Similarly, the updating of priorities and / or quality criteria of terrestrial areas and / or weight of discrete acquisition opportunities can be performed at the last moment before solving the optimization problem.
    In a step 500, following step 400, an optimum sequence of discrete acquisition opportunities having a maximum weight, and kinematically compatible, is determined.
    Said optimal sequence is sought within the graph G by traversing the portion situated above the diagonal of the matrix M according to a longer path calculation method, and provides a theoretical acquisition plan followed by the satellite during his mission of observation.
    To do this, we proceed in two stages. In a first step, for each discrete acquisition opportunity D1 of the set D, an objective objective weight (D ') is determined, which is the maximum weight of the kinematically compatible sequences and leading to the discrete acquisition opportunity D1. For this, we introduce a set P (D ') of all the discrete acquisition opportunities preceding D1 in the set D, and kinematically compatible with D1. Then the objective weight obj (D ') is equal to the weight of D1 to which is added the maximum of the objective weights of the discrete acquisition opportunities of P (D'), that is to say obj {D ') = c [D '] + maxsep (Di} (oèy (s)).
    Now assuming that the set D is of cardinal Q (D), and introducing a variable previous {D) which stores the opportunity of discrete acquisition of the set P (D ') maximizing the weight of the optimal sequence leading to D1, the determination of the objective weight of all the elements of the set D is done dynamically by means of a first algorithm with:
    For i ranging from 1 to Q (D); obj (Ci) = c [D '] End of Pour;
    For i ranging from 1 to Q (D); previous (D ') = -1 End of For;
    For i ranging from 1 to Q (D);
    For j ranging from (i + 1) to Q (D);
    Si = 1:
    If obj (Ü) + c [D ']> obj (Di): previous (Ü) = Ü; obj (Ü) = obj (D ') + c [Ü];
    End of Si;
    End of Si;
    End of For;
    End of For;
    It should be noted that the search for the optimal sequence by the method of calculating the longest path, as presented in the first algorithm, is advantageously adapted to the fact that the discrete acquisition opportunities of D are classified by increasing start dates. in the course of step 300. Indeed, such a classification corresponds to a topological order on the graph G which facilitates the implementation of the sequential steps of said first algorithm.
    In a second step, said optimal sequence is determined by selecting among the discrete acquisition opportunities of D, that of maximum objective weight, then iteratively going up the predecessors of said opportunity of maximum objective weight by means of the information stored in the variable previous .
    As noted above, the classification of the discrete acquisition opportunities of D advantageously provides a topological order on the graph G, which is then acyclically oriented, and consequently any kinematically compatible sequence obtained at the output of step 500 is optimal. in the sense of maximality of weight.
    In a particular mode of implementation of the method, the step 500 comprises for each discrete acquisition opportunity D1 of the set D a partial selection of discrete acquisition opportunities preceding D1 in the set D, and kinematically compatible. with D1, among all the discrete acquisition opportunities preceding D1 in the set D, and kinematically compatible with D1.
    Such a procedure is to restrict the set P (D ') for each discrete acquisition opportunity D1 of the set D. Thus, said set P (D') can be advantageously replaced by a set PC (D ') ) defined as a subset of the latter, and comprising the discrete acquisition opportunities preceding D1 in the set D, kinematically compatible with D1 as well as close to D1. By relatives of D1, it is understood here that the elements of PC (D ') respectively occupy a position in D so that the difference between this position and that of D1 remains bounded by a predefined constant. Therefore, the objective weight obj (D ') is obtained by the formula obj {D') = c [D '] + maxsePc (Di} (oe; (s)). To this end, we introduce a variable maxNextVertice (D ') which contains for each acquisition opportunity D1 the maximum number of vertices of the graph G visited during the search for the optimal sequence The scalar maxNextVertice (D') thus constitutes a cardinal enhancer of the set PC (D ') Therefore, the first algorithm becomes:
    For i ranging from 1 to Q (D); obj (Ci) = c [D '] End of Pour;
    For i ranging from 1 to Q (D); previous (D ') = -1 End of For;
    For i ranging from 1 to Q (D);
    For j ranging from (i + 1) to maxNextVertice (Ü):
    If Mu = 1:
    If obj (Ü) + c [D ']> obj (Di): previous (Ü) = Ü; obj (Ü) = obj (D ') + c [Ü];
    End of Si;
    End of Si;
    End of For;
    End of For;
    Limiting the set P (D ') to the set PC (D') is advantageous because the exploration of the vertices of G by the method of calculating longer path is reduced in computation time. For example, and in no way limiting, when the set PC (D ') contains only discrete acquisition opportunities separated by not more than sixty seconds of D' along the scrolling orbit, the computation time is reduced by 60% to 70% and the optimal sequence remains unchanged compared to the case where PC (D ') is not used.
    FIG. 2 represents a preferential mode of implementation of the method of FIG. 1 during which the method comprises, following step 500, a step 600 of verification of respect of at least one cumulative constraint imposed on said satellite .
    A cumulative constraint imposed on the satellite is a constraint that takes into account all the choices made in the planning of the observation mission before the satellite reaches its orbit a discrete acquisition opportunity. In other words, and in opposition to the kinematic local constraints associated with each discrete acquisition opportunity, a cumulative constraint has a global character relative to the mission history of the satellite.
    For example, and in no way limiting, said at least one cumulative constraint includes a memory size constraint. In fact, on an observation mission, the satellite stores in digital format the acquisitions it realizes in a memory of a type known per se and of limited size.
    Alternatively or in addition to step 600, said at least one cumulative constraint comprises a consumed electric power constraint. Indeed, on an observation mission, the satellite consumes to move electrical energy stored in batteries of limited respective capacities. It is the same for the operation of the optics of the satellite. It should be noted that said batteries are rechargeable by means generally of solar panels.
    Alternatively or in addition to step 600, said at least one cumulative constraint includes a maximum time constraint for operating instruments embedded in said machine.
    Nothing excludes, according to other examples not detailed here, to have other cumulative constraints applied to the satellite.
    The verification of said at least one cumulative constraint consists in validating that the optimal acquisition sequence obtained at the output of step 500 is compatible with the general operation of the satellite. For this purpose, this verification is carried out during step 600 by means, for example, of an iterative process consisting in deleting one by one of said optimal sequence the discrete acquisition opportunities in order of increasing priority both that said at least one cumulative constraint is not satisfied. In this way, the method produces at the output of step 600 a sequence which is a subsequence of the optimal sequence obtained at the output of step 500, and which is compatible with the cumulative constraints associated with the satellite. This sequence obtained at the output of step 600 is the acquisition plan actually followed by the satellite during its mission.
    FIG. 3 represents a particular mode of implementation of the method of FIG. 1 during which the method may comprise a step 50 of aggregation of terrestrial areas, prior to step 100 of determining discrete acquisition opportunities.
    By aggregation of terrestrial areas, here is meant the grouping of certain terrestrial zones Z-ι, ..., Ζν, within one or more so-called enclosing zones, said grouped zones having to be geographically close to one another, maximize the number of zones acquired during the same discrete acquisition opportunity.
    For example, a skimming zone may contain a plurality of terrestrial areas aligned in the direction of acquisition of the satellite along its orbit.
    In another example, possibly coupled to the preceding one, a bounding zone may contain a plurality of terrestrial areas aligned in a direction transverse to the orbit of the satellite. In this case, the size of said bounding zone is limited by the size of the swath of the satellite.
    In the implementation of step 50, each encompassing zone is for example associated with a priority equal to the priority of highest importance among the priorities of all the zones grouped within said encompassing zone. In addition, the quality criterion of an encompassing zone is for example equal to the sum of the respective quality criteria of the zones grouped within said bounding zone. At the end of step 50, each bounding zone is viewed as a separate terrestrial area so that steps 100 to 600 are not modified.
    It should be noted that the grouping of terrestrial areas within bounding areas is relevant when several terrestrial areas are contiguous, so that all of them can be acquired at one time. Such a procedure is advantageous because it allows the satellite to save the necessary maneuvering time otherwise to move between the discrete acquisition opportunities respectively associated with each of said grouped terrestrial areas. This saving of time can advantageously be used to acquire more land areas that can not be grouped within encompassing areas.
    FIG. 4 represents a preferential mode of implementation of the method of FIG. 1 during which the step 500 of determination of an optimal sequence advantageously comprises the dynamic update of a pathMesh variable storing the zones Z, associated with the discrete acquisition opportunities of said optimal sequence, so as to prevent the duplication of opportunities for discrete acquisition of areas to be acquired once. For this purpose, by noting mesh (D ') the function that returns the terrestrial area with which the discrete acquisition opportunity D' is associated, the first algorithm is rewritten as follows:
    For i ranging from 1 to Q (D); obj (Ci) = c [D '] End of Pour;
    For i ranging from 1 to Q (D); previous (Ü) = -1 End of For;
    For i ranging from 1 to Q (D);
    For j = (i + 1) ... maxNextVertice ([y):
    If Mu = 1:
    If obj (Ü) + c [Ü]> obj (Ü):
    If mesh (Ü) ¢. pathMesh ([y]; previous (Ü) = ΰ; obj (Di) = obj (d) + c [Ü]; pathMesh ([y) = {pathMesh (D ') mesh ([y)};
    End of Si;
    End of Si;
    End of Si;
    End of For;
    End of For;
    By storing in the pathMesh variable the history of the terrestrial areas visited during the determination of the optimal sequence, the method is advantageously adapted to prevent a terrestrial zone Z, having a high quality criterion, associated with a high priority request as well as that to be acquired only once, is finally acquired a plurality of times. Indeed, assuming that such a zone Z is associated with several discrete acquisition opportunities kinematically compatible with each other, the method of calculating the longest path seeking to maximize the weight of the optimal sequence, it is quite possible that several of the discrete acquisition opportunities associated with Z, are included in said optimal sequence. It is therefore advantageous to introduce the pathMesh variable as explained above in order to discriminate this type of configuration.
    The characteristics detailed above make it possible to obtain an optimal sequence guaranteeing a single shooting for each terrestrial zone associated with a single-vision request. It remains to consider also the case of terrestrial areas associated with stereo / tri-stereo requests. Therefore, in said preferred mode of implementation illustrated in FIG. 4, the method also comprises a step 450 for taking into account multiple acquisition requests, following the kinematic compatibility evaluation step 400 and prior to step 500 of determining an optimal sequence, wherein the respective weights of discrete acquisition opportunities associated with Z areas to be acquired a plurality of times are updated and in which a mustHit variable forces concatenation of said discrete acquisition opportunities in order to satisfy said requests for multiple acquisitions.
    It should be noted that the discrete acquisition opportunities associated with a zone Z, to be acquired a plurality of times belong to the same time interval of visual accessibility T, and are furthermore distinct from each other. Said opportunities therefore have different start dates and thus make it possible, for example, to acquire said Z zone from a different angle.
    The general principle of step 450 consists in artificially increasing the double or triple the weight of the discrete acquisition opportunities associated with zones Z, to be acquired respectively in stereo or tri-stereo mode. It is also understood that the agility of the satellite makes it possible to consider satisfying single-channel requests between acquisition opportunities associated with zones Z, to be acquired several times.
    For this purpose, it is first determined, for each request corresponding to a request for multiple acquisitions, all the kinematically compatible acquisition sequences, comprising exactly the number of acquisitions required so as to satisfy said request (this number is 2 and 3 respectively in the stereo and tri-stereo cases), as well as possibly discrete acquisition opportunities associated with other single-ended requests as discussed above. Such a sequence is called a multi-acquisition sequence and is constructed so that its first and last elements are discrete acquisition opportunities belonging to the same terrestrial area and associated with the request on which said multi-acquisition sequence depends. In other words, said first and last elements are not associated with single-channel requests.
    In a second step, for each multi-acquisition sequence as determined above: - a chaining criterion is determined. Said chaining criterion is a scalar that corresponds to a measure of the interest of satisfying the request with which said multi-acquisition sequence is associated with actually said multi-acquisition sequence rather than another. The chaining criterion is therefore a comparison scale of the multi-acquisition sequences associated with the same request, - a chaining weight is determined. In a particular mode of implementation, said weight of chaining depends on the priority of the request, the quality criterion w [Z,] of the zone Z, associated with said request as well as said criterion of chaining. For example, the consideration of said chaining criterion in the chaining weight is done by adding said chaining criterion to the quality criterion w [Z,] in a manner identical to that described in step 100 concerning the use of the acquisition interest criterion w [a {]. Therefore, the chaining weight of the multi-acquisition sequence is a vector of which only one component is non-zero, - the graph G is updated according to a graph Gmuiti · On the one hand, the graph Gmuiti has corresponding vertices respectively the discrete acquisition opportunities associated with single-channel requests and respectively having a weight as determined in step 100. On the other hand, the Gmuiti graph comprises vertices respectively corresponding to each discrete acquisition opportunity of said multi-stage sequence. acquisition and all having a zero weight, except the vertex associated with the first component of said sequence and whose weight is equal to the weight of chaining, - one creates a mustHit variable which at each discrete acquisition opportunity of said multi-acquisition sequence associates the discrete acquisition opportunity that succeeds in time within said multi-acquisition sequence. For example, in no way limiting, if said multi-acquisition sequence is associated with a tri-stereo request of a zone Z, and is written (af, af, af), then mustHit {af) = af and mustHit {af) = af. In another example, and in no way limiting, if said multi-acquisition sequence is associated with a tri-stereo request of a zone Z, and is written (af, af, af, af), where af is an opportunity associated with a single-field query of a zone Zj different from Z ,, then we have mustHit {af) = af, mustHit {af) = af and mustHit {af) = af.
    It should be noted that in the case where a request corresponding to a request for multiple acquisitions is associated with several possible multi-acquisition sequences, the Gmuiti graph comprises vertices corresponding to identical discrete acquisition opportunities in terms of the start date. but nevertheless different from each other in terms of weight. For example, and in no way limiting, suppose that a stereo request is associated with a discretized accessibility interval according to four discrete acquisition opportunities (af, af, af, af) so that only the multi-acquisition sequences ( af, af) and (af, af) are kinematically compatible and adapted to satisfy said request. Then the vertex af will appear twice in the Gmuiti graph, namely a first time with a weight equal to the chaining weight of the sequence (af, af) and so that mustHit {af) = af, as well as a second times with a weight equal to the chaining weight of the sequence (af, af) and so that mustHit {a ) = af. The vertices af, af and af only appear once in the Gmuiti graph and have zero weight.
    The graph Gmuiti is represented by means of a matrix Mmuiti according to a mode of implementation identical to that used to represent the graph G by means of the matrix M in the step 400. It is thus understood, because certain opportunities of Discrete acquisition can appear several times in the Gmuiti graph as described above, that said matrix MmU | tj has a size greater than the matrix M. Moreover, the graph Gmuiti is the one used during the step 500 of searching for an optimal sequence when the set of requests transmitted to the satellite comprises at least one request for multiple acquisitions.
    Furthermore, the mustHit variable is also adapted to force the execution of a multi-acquisition sequence once the first element of the latter is effectively integrated into the optimal sequence during step 500. Such a procedure is advantageous because it allows the process to take into account in their entirety the requests associated with requests for multiple acquisitions without favoring the latter to the detriment of single-channel requests with discrete acquisition opportunities of greater respective weight opportunities that include said requests for multiple acquisitions.
    The mustHit variable is also advantageously used during the calculation of the longest path of step 500 in order to verify that when a discrete acquisition opportunity is added to the optimal sequence under construction, this discrete acquisition opportunity is well stored. in the mustHit variable applied to the elements of the optimal sequence preceding the added opportunity.
    In the case of a satellite constellation, it is advantageous to be able to respond quickly to a client if a request can be made and under what time. In this case, the method can be: a) reception of the client's request, b) identification of the next satellite that can make this acquisition, without taking into account the current acquisition plan of this satellite; c) generation of a new plan for said satellite with the following constraints: c1. all acquisitions scheduled in the current plan must remain (unless we agree to cancel planned acquisitions), however their acquisition conditions may change. c2. insertion of the new request d) according to the result of the optimization: d1. if the acquisition is included in the new plan then the modified plan is transmitted to satellite d2. otherwise we reiterate on the next satellite
    It is not necessary to take the new customer requests one by one, this can be done periodically, for example every 5 minutes. With a suitable choice of priorities, it is possible to force the consideration of the new request.
    Because of its speed, the calculation of the plan can be done frequently. In addition, the update of the solution is less expensive than a complete calculation starting from the results of the preceding calculation, and in particular the matrix M representing the graph obtained at the end of step 400 or the graph Gmuit associated with the Mmuiti matrix at the end of step 450
    Thus, it is possible to minimize the calculation time for the steps prior to step 500, which are the most time-consuming for calculation.
    权利要求:
    Claims (21)
    [1" id="c-fr-0001]
    1. A planning method for acquiring images of terrestrial zones Z-ι, ..., Ζν, by a spacecraft in mission around the Earth following a predetermined scrolling orbit, such as for example an observation satellite, each terrestrial zone Z, being associated with a request R, of priority p, so that at said zone Z, there corresponds a temporal interval of visual accessibility T, along said moving orbit, characterized in that it comprises the steps following successive steps: - a step (100) for determining, for each interval T, discrete acquisition opportunities of the zone Z, so that each discrete acquisition opportunity is associated with a start date included in said interval T ,, a running time, a kinematic local stress as well as a weight, - a step (200) of grouping discrete acquisition opportunities Z zones, in a set D, - a step (300) of ranking the discrete acquisition opportunities of the set D, the acquisition opportunities being classified by increasing start date and designated by D ', - a step (400) of cinematic compatibility evaluation between said discrete acquisition opportunities of the set D, taken in pairs according to their respective rankings, - a step (500) of determining an optimum sequence of discrete acquisition opportunities having a maximum weight, and kinematically compatible.
    [2" id="c-fr-0002]
    2. Method according to claim 1, comprising a step (450) for taking into account multiple acquisition requests, subsequent to the kinematic compatibility evaluation step (400) and prior to the determination step (500). an optimal sequence, in which the respective weights of discrete acquisition opportunities associated with zones Z, to be acquired a plurality of times are updated and in which a mustHit variable forces the sequence of said discrete acquisition opportunities to satisfy said requests for multiple acquisitions.
    [3" id="c-fr-0003]
    3. Method according to one of claims 1 to 2, wherein the step (500) of determining an optimal sequence comprises the dynamic update of a pathMesh variable storing zones Z, associated with acquisition opportunities discrete of said optimal sequence, so as to prevent the duplication of discrete acquisition opportunities of areas to be acquired once.
    [4" id="c-fr-0004]
    4. Method according to one of claims 1 to 3, wherein the step (500) comprises for each discrete acquisition opportunity D 'of the set D a partial selection of discrete acquisition opportunities preceding D' in D, and kinematically compatible with D ', among all the discrete acquisition opportunities preceding D' in D, and kinematically compatible with D '.
    [5" id="c-fr-0005]
    5. Method according to one of claims 1 to 4, comprising a step (600) for checking compliance with at least one cumulative constraint imposed on said spacecraft, said verification step (600) being consecutive to step (500). ) of determining an optimal sequence.
    [6" id="c-fr-0006]
    The method of claim 5, wherein said at least one cumulative constraint has a memory size constraint.
    [7" id="c-fr-0007]
    7. Method according to one of claims 5 to 6, wherein said at least one cumulative stress comprises a consumed electric power constraint.
    [8" id="c-fr-0008]
    8. Method according to one of claims 5 to 7, wherein said at least one cumulative stress comprises a maximum time constraint of operation of instruments embedded in said machine.
    [9" id="c-fr-0009]
    The method according to one of claims 5 to 8, wherein the cumulative constraint compliance checking step (600) comprises dynamically updating said optimal sequence by suppressing discrete acquisition opportunities, as long as said cumulative constraints are not satisfied.
    [10" id="c-fr-0010]
    10. Method according to one of claims 1 to 9, wherein the start dates of the discrete acquisition opportunities of each interval T are sampled temporally in a constant time step.
    [11" id="c-fr-0011]
    11. The method of claim 10, wherein the respective time steps of the intervals Ti, ..., Tn are equal to each other.
    [12" id="c-fr-0012]
    The method of claim 10, wherein the respective time steps of at least two intervals Tj and Tj are different.
    [13" id="c-fr-0013]
    The method of claim 10, wherein the time step of each interval T is adjusted so that said interval T is associated with 20 discrete acquisition opportunities.
    [14" id="c-fr-0014]
    14. Method according to one of claims 1 to 13, wherein the kinematic local stress of a discrete acquisition opportunity comprises an attitude setpoint of said spacecraft at the beginning and end of said discrete acquisition opportunity.
    [15" id="c-fr-0015]
    15. The method as claimed in one of claims 1 to 14, in which the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority p, of the request R, associated with said zone Z,.
    [16" id="c-fr-0016]
    16. Method according to one of claims 1 to 15, wherein each zone Z is associated with a quality criterion w, depending on the geometrical characteristics of said zone Z, as well as the meteorological conditions expected during the time interval d visual accessibility Ti.
    [17" id="c-fr-0017]
    The method of claim 16, wherein the weight of each discrete acquisition opportunity associated with a zone Z, depends on the priority p, of the request R, so as to be a vector whose only non-zero component is equal. the criterion quality w ,, the position of said non-zero component in said vector depending on the priority of said request R ,.
    [18" id="c-fr-0018]
    18. The method of claim 17, wherein said non-zero component depends on the quality criterion w, and a criterion of acquisition interest associated with said discrete acquisition opportunity.
    [19" id="c-fr-0019]
    19. Method according to one of claims 17 to 18, wherein the step (500) of determining an optimum sequence comprises a comparison of respective weights of discrete acquisition opportunities cinematically compatible with each other.
    [20" id="c-fr-0020]
    20. Method according to one of claims 1 to 19, comprising a step 50 of aggregation of terrestrial areas, prior to step 100 of determining discrete acquisition opportunities.
    [21" id="c-fr-0021]
    21. Method according to one of claims 1 to 20, wherein said spacecraft is an observation satellite operating in a comb mode.
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    优先权:
    申请号 | 申请日 | 专利标题
    FR1557215A|FR3039728B1|2015-07-28|2015-07-28|METHOD FOR PLANNING THE ACQUISITION OF IMAGES OF TERRESTRIAL AREAS BY A SPACE DEVICE|FR1557215A| FR3039728B1|2015-07-28|2015-07-28|METHOD FOR PLANNING THE ACQUISITION OF IMAGES OF TERRESTRIAL AREAS BY A SPACE DEVICE|
    US15/748,172| US10392133B2|2015-07-28|2016-07-28|Method for planning the acquisition of images of areas of the earth by a spacecraft|
    EP16763887.3A| EP3328736B1|2015-07-28|2016-07-28|Method for planning the acquisition of images of areas of the earth by a spacecraft|
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    CA2993926A| CA2993926C|2015-07-28|2016-07-28|Method for planning the acquisition of images of areas of the earth by a spacecraft|
    PCT/FR2016/051963| WO2017017384A1|2015-07-28|2016-07-28|Method for planning the acquisition of images of areas of the earth by a spacecraft|
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