System and method for multi-mission planning of remote sensing data acquisition

Abstract

A system and method for multi-mission planning of remote sensing is provided herein. A system for multi-mission planning performs integrated optimized scheduling of multiple heterogenous satellite missions. The system generates multi-mission acquisition schedules, a set of optimized and de-conflicted satellite schedules that satisfy specific satellite constraints and adhere to mission-specific operational environments.

Description

SYSTEM AND METHOD FOR MULTI-MISSION PLANNING OF REMOTE SENSING DATA ACQUISITIONTechnical Field

[0001] The following relates generally to satellite-based Earth observation, and more particularly to systems and methods for multi-mission planning for satellite-based Earth observation.Introduction

[0002] The number of Earth-observation satellite constellations has been steadily increasing. Many organizations and governments already own several satellite constellations with plans for further expansions in the coming decades.

[0003] At the same time, the satellite imagery demand has been outpacing the supply of imaging capacity. In this environment, new problems arise. The set of orders to be submitted to one satellite mission should be de-conflicted before the submission to this downstream mission. In addition, to decrease latency, it may be beneficial to submit portions of an order to more than one downstream mission.

[0004] It is desired to streamline and speed up the access to multiple satellite missions and make such access more convenient and straightforward.

[0005] Accordingly, there is a need for improved systems and methods for multimission planning that overcome at least some of the disadvantages of existing systems and methods.Summary

[0006] Systems and methods for multi-mission planning of remote sensing data acquisition are provided herein. A system for multi-mission planning performs integrated optimized scheduling of multiple heterogenous satellite missions. The system generates optimized multi-mission schedule, a set of optimized and de-conflicted satellite schedules that satisfy specific satellite constraints and adhere to mission-specific operational environments.

[0007] In an embodiment, a system for multi-mission planning includes a scheduler graphical user interface (GUI), a schedule manager, an area of interest (AOI) coverage planner, an opportunity generator, an acquisition order database, an acquisition request data service, a sensor service, an acquisition schedule data service, and an acquisition schedule optimizer.

[0008] A method of automated multi-mission planning of satellite imagery acquisition is provided. The method includes: storing a list of admissible satellites and beam modes; receiving an image acquisition request that includes a requested area of interest (“AOI”) and a requested period of interest or time range; generating a set of imaging opportunities from the image acquisition request, wherein each imaging opportunity specifies a start time, and end time, and a sensor, wherein the set of imaging opportunities cover the requested AOI within the request period of interest using the admissible satellites and beam modes; generating at least one AOI coverage plan using the acquisition request and the set of imaging opportunities, wherein the at least one AOI coverage plan includes a set of imaging strips covering the requested AOI and the set of imaging opportunities for the requested AOI, wherein each imaging strip corresponds to a portion of a satellite swath of an admissible satellite that intersects with the requested AOI, and wherein each imaging strip specifies an area, a spec, and a sensor; providing (i) the image acquisition request and at least one coverage plan, and (ii) a set of satellites and satellite missions and their availability, to an acquisition schedule optimizer; and generating, via the acquisition schedule optimizer, a set of deconflicted acquisition schedules including one schedule for each available satellite, using one or more optimization algorithms.

[0009] In an embodiment, the image acquisition request further specifies a geometry, a mode, and a sensor.

[0010] In an embodiment, the requested AOI is characterized by one or more of: a request priority specifying a priority of the user and importance of the task; a satellite or sensor, potentially with preference values; a resolution, mode, and polarization, potentially with preference values; a range of incidence angles; one or more look directions, the look directions being left-looking or right-looking; a pass direction indicatingan ascending pass (from South to North) and / or a descending pass (from North to South); and repeated imaging or a standing order (e.g., daily, weekly repeat cycle).

[0011] In an embodiment, each imaging opportunity further specifies a satellite, an orbit, the image acquisition request, a strip, and an area of the strip.

[0012] In an embodiment, each imaging opportunity includes: a time window; an associated satellite, orbit, mode, and geometry (e.g., incidence angle); an associated imaging strip and request; observation (imaging) duration for the imaging strip associated with the imaging opportunity with the associated satellite, mode, and geometry; quality of imaging including how well the imaging opportunity on the satellite satisfies the requirements of the image acquisition request.

[0013] In an embodiment, the AOI coverage plan covers all of the requested AOI.

[0014] In an embodiment, the AOI coverage plan covers a portion of the requestedAOI that meets a coverage threshold that is less than 100%.

[0015] In an embodiment, the coverage threshold is configured by a user through a graphical user interface.

[0016] In an embodiment, the at least one AOI coverage plan is a plurality of AOI coverage plans, and the method further includes assigning a score to each of the plurality of AOI coverage plans and ranking the plurality of AOI coverage plans for the image acquisition request according to the assigned scores.

[0017] In an embodiment, the method further includes dividing each schedule in the set of acquisition schedules into separate orders and, for each satellite mission, submitting the separate orders to a planning system of that satellite mission.

[0018] In an embodiment, the method further includes receiving an acquisition order from a centralized ordering system and translating one or more tasks in the acquisition order into the image acquisition request.

[0019] In an embodiment, the acquisition order defines a type of imagery, a time, a location, and a collecting source.

[0020] In an embodiment, the AOI coverage plan includes plan quality data indicating how well the AOI coverage plan satisfies the image acquisition request, and the plan quality data includes one or more of a measure of how compatible selected satellites are for the image acquisition request, how much of the AOI is covered by the AOI coverage plan, and how much overlap there is among the set of imaging strips.

[0021] the one or more optimization algorithms include one or more greedy heuristic algorithms, one or more improvement heuristic algorithms, and one or more exact optimization algorithms.

[0022] In an embodiment, the method further includes using a first of the one or more optimization algorithms for a fast-tasking scenario and a second of the one of more optimization algorithms for a routine planning scenario.

[0023] In an embodiment, the one or more optimization algorithms include one or more of: a greedy construction heuristic, a local search algorithm, a tabu search algorithm, a variable neighborhood search algorithm, and an exact optimization algorithm.

[0024] In an embodiment, for each satellite, the acquisition schedule includes: a list of opportunities each with a start time and end time of the observation (imaging) of the associated strip; and the maneuver time and activity including starting pointing location and ending pointing location of the camera / sensor.

[0025] In an embodiment, the method further includes generating a spacecraft control schedule based on the set of deconflicted acquisition schedules and sending the spacecraft control schedule to the satellite.

[0026] In an embodiment, the method further includes generating an order based on the set of deconflicted acquisition schedules and sending the order to a ground segment of a downstream satellite mission.

[0027] Other aspects and features will become apparent, to those ordinarily skilled in the art, upon review of the following description of some exemplary embodiments.Brief Description of the Drawings

[0028] The drawings included herewith are for illustrating various examples of articles, methods, and apparatuses of the present specification. In the drawings:

[0029] Figure 1 is a schematic diagram of an Earth observation and geointelligence system, according to an embodiment;

[0030] Figure 2 is a block diagram of a multi-mission planning system, according to an embodiment;

[0031] Figure 3 is a block diagram of the schedule manager and acquisition schedule optimizer of Figure 2, showing the acquisition schedule optimizer in greater detail, according to an embodiment;

[0032] Figure 4 is a high-level flow diagram of a method of generating a deconflicted multi-mission acquisition schedule, according to an embodiment;

[0033] Figure 5 is a detailed flow diagram of a method of generating de-conflicted optimized schedules, according to an embodiment; and

[0034] Figure 6 is a flow diagram of a method of generating an AOI coverage plan, according to an embodiment.Detailed Description

[0035] Various apparatuses or processes will be described below to provide an example of each claimed embodiment. No embodiment described below limits any claimed embodiment and any claimed embodiment may cover processes or apparatuses that differ from those described below. The claimed embodiments are not limited to apparatuses or processes having all of the features of any one apparatus or process described below or to features common to multiple or all of the apparatuses described below.

[0036] One or more systems described herein may be implemented in computer programs executing on programmable computers, each comprising at least one processor, a data storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. For example,and without limitation, the programmable computer may be a programmable logic unit, a mainframe computer, server, and personal computer, cloud-based program or system, laptop, personal data assistance, cellular telephone, smartphone, or tablet device.

[0037] Each program is preferably implemented in a high-level procedural or object-oriented programming and / or scripting language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Each such computer program is preferably stored on a storage media or a device readable by a general or special purpose programmable computer for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein.

[0038] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the present invention.

[0039] Further, although process steps, method steps, algorithms or the like may be described (in the disclosure and I or in the claims) in a sequential order, such processes, methods and algorithms may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any order that is practical. Further, some steps may be performed simultaneously.

[0040] When a single device or article is described herein, it will be readily apparent that more than one device I article (whether or not they cooperate) may be used in place of a single device I article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device I article may be used in place of the more than one device or article.

[0041] The following relates generally to satellite-based earth observation, and more particularly to systems and methods for multi-mission planning for satellite-based earth observation.

[0042] Systems and methods of the present disclosure may be implemented at one or more computer devices. For example, the system may include a plurality of computer devices in communication via a network connection. Further, components of the system (e.g., modules, data hubs, etc.) may be implemented at a single computer device, or across a plurality of computer devices. In some embodiments, the system includes at least one user computing device and at least one server computing device in communication via a network connection. The user device may execute an application that can interact with server-side software components (“services”) hosted by the server computing device. For example, the computer system may execute a network-based software application that executes partially at the server computing device (via serverside software components) and partially at the user device (via client-side software components). In an embodiment, the client-side software components include a user interface (e.g., web-based user interface).

[0043] As used herein, the term “mission” (as in multi-mission) may refer to a satellite constellation (i.e. , a group of artificial satellites working together as a system). In some cases, a mission may include only one satellite, while in other cases a mission may include a plurality (e.g., several) satellites. The present disclosure provides a multimission capability that enables combining missions for more efficient planning and scheduling.

[0044] Referring now to Figure 1 , shown therein is a system 100 for earth observation, according to an embodiment.

[0045] The system 100 includes a space segment 102 and a ground segment 104. Ground segment 104 has multi-mission planning capabilities (e.g., via components 108, 114, 116, and 124, described below). The system 100 further includes one or more other ground segments 804 and one or more other space segments 802. The multi-mission planning system of ground segment 104 can communicate with other ground segments 804 for accessing other satellite constellations (missions) (i.e., other space segments 802) that are not in direct communication with ground segment 104. Ground segments 804 have direct communication through a ground terminal (antenna) to another set of satellites (in other space segments 802). The multi-mission planning capabilities providedby ground segment 104 (and, in particular, computer system 122, described below) allow planning for all space segments (within 102 and 802).

[0046] The space segment 102 includes a plurality of satellite-based sensor data collectors 106. While a single satellite-based sensor data collector 106 is shown in Figure 1 , the number of satellite-based sensor data collectors 106 may vary and is not particularly limited. The satellites 106 may be a satellite constellation or plurality of satellite constellations.

[0047] Further, the satellite-based sensor data collectors 106 may collect one or more types of sensor-based earth observation data. Accordingly, each satellite-based sensor data collector 106 is equipped with at least one sensor type for collecting sensor data according to that sensor type. Example sensor types include, without limitation, optical sensors (e.g., high resolution optical) and SAR sensors. The sensor data may be signal-level maritime domain surveillance data. The data collected by the satellites 106 may also be referred to as imagery (not limited to optical) or remote sensing data.

[0048] The plurality of satellite data sources 106 communicate with a ground station 108 via an uplink 110 and downlink 112. The manner of communication is generally known. In other embodiments, there may be a plurality of ground stations 108 and the number of ground stations 108 is not particularly limited. The ground stations may be located in multiple geographic locations.

[0049] The ground station 108 includes an antenna system and a data processing device. The ground station 108 communicates with the satellites 106 via the antenna system. The ground station 108 may receive signal-level data from the satellite 106.

[0050] The data processing device of the ground station 108 processes data to be sent to the satellites 106 and processes data received from the satellites 106.

[0051] The ground segment 104 further includes a server 114 and a user device 116. While a single server 114 and single user device 116 are shown in Figure 1 , the number of servers 114 and user devices 116 may vary (e.g., multiple) and the number is not particularly limited.

[0052] The user device 116 is configured to receive input from a user and display data generated by the server 114. The input data received from a user may be used to request certain data generated and stored by the server 114. The user device 116 is configured to display a graphical user interface that allows a user to interact with the server 114. The user interface may include a series of user interface screens for receiving user input and display output data generated by the server 114.

[0053] The user device 116 and the server 114 communicate via a network 118. The network 118 may be a wide area network, such as the Internet. The data processing device of the ground station 108 communicates with the server 114 and, in some cases, the user device 116, via the network 118. Communication in this context may include sending and receiving data.

[0054] The ground segment 104 further includes a multi-mission planning software application 120. The multi-mission planning software application 120 includes server-side software components executing at the server 114 and client-side software components executing at the user device 116. The client-side software components include a graphical user interface for displaying data generated by the application 120 at the server 114 and for receiving input data from a user.

[0055] The server 114 and user device 116 may together be referred to as computer system 122. The server 114 may receive orders from an ordering computer system 124 executing an ordering software application 126. The orders may indicate users’ desires for satellite-based imagery. The orders may define certain parameters, such as a type of imagery, a time, a location, a collecting source, etc.

[0056] The computer system 122 allows for streamlined ordering from multiple sources of EO (Earth Observation) imagery (e.g., satellites 106 or other ground segments).

[0057] The computer system 122 provides effective decision-making capabilities that aid the distribution of incoming orders to appropriate downstream satellites or satellite missions (represented by ground segments 800). The computer system 122 supports the division into disjoint de-conflicted sets of mission orders that can be sent to downstream missions. An order may be divided and distributed to two or more missions.

[0058] As such, the computer system 122 may reduce delays and decrease rejections from downstream missions 802, 804. The computer system 122 is configured to generate de-conflicting acquisition schedules serving incoming orders and adhering to the missions’ constraints.

[0059] The computer system 122 is configured to provide centralized and integrated acquisition planning for multiple satellites 106 and satellite constellations and missions including 802 and 804. The computer system 122 may execute optimization algorithms and models for solving the multi-mission acquisition planning / scheduling problem.

[0060] Referring now to Figure 2, shown therein is a system 200 for multi-mission planning of remote sensing data acquisition, according to an embodiment.

[0061] The system 200 may be the computer system 122 of Figure 1. The computer system 200 may be implemented across one or more devices. For example, the portions of the computer system 200 may be implemented at the server 114 and user device 116 of Figure 1 .

[0062] Features and functionalities of the computer system 200 may be encoded as computer-executable instructions (e.g., application 120 of Figure 1 ) to be executed by one or more processors (e.g., at device 114, 116 of Figure 1 ).

[0063] The system 200 includes a multi-mission planning system (MMPS) 202 that is in communication with a centralized ordering system 204 (e.g., ordering device 124 of Figure 1 ) and downstream missions 206 and other ground segments 802 (e.g., satellites 106 and ground station 108 of Figure 1 ). Components 202, 204, 206 may communicate with one another via network 118 of Figure 1 .

[0064] Generally, the MMPS 202 performs integrated optimized scheduling of multiple heterogeneous satellite missions. Integrated acquisition scheduling balances the utilization of satellite resources and may satisfy a larger number acquisition requests in a shorter time frame. Integration of scheduling has a potential of increasing the overall operational performance of satellite resources significantly compared to the optimized scheduling of each satellite mission separately.

[0065] When an acquisition request is fully scheduled by the MMPS 202, each portion of the request’s area of interest (AOI) is covered by a portion of a satellite swath that intersects with its AOI, called strip. Each strip has a geographic footprint and there may be different opportunities for imaging the strip in different time intervals, e.g., by different satellites of the same constellation. The set of strips covering the AOI are considered as an AOI coverage plan. The AOI coverage plan can be generated in advance or can be a result of the series of scheduled acquisitions that cover entire AOI.

[0066] The MMPS 202 generates multi-mission schedule, optimized and deconflicted satellite schedules that satisfy the specific satellite constraints and adhere to mission-specific operational environments.

[0067] The MMPS 202 receives acquisition orders from the ordering system 204 and sends acquisition orders statuses to the ordering system 204.

[0068] The MMPS 202 sends mission-specific orders to the downstream missions 206 and receives mission order acquisition status rejections from the downstream missions 206.

[0069] The MMPS 202 includes a scheduler graphical user interface (GUI) 210, a schedule manager 212, an area of interest (AOI) coverage planner 214, an opportunity generator 216, an acquisition order database 218, an acquisition request data service 220, a sensor service 222, an acquisition schedule data service 224, and an acquisition schedule optimizer 226.

[0070] The scheduler GUI 210 may be implemented at user device 116 of Figure 1 . The scheduler GUI 210 enables interaction with a user 228, who may be referred to as mission planner. The GUI 210 is configured to receive input data from the user 228 and display data generated by MMPS 202 to the user 228.

[0071] The scheduler GUI 210 communicates with the schedule manager 212. The scheduler GUI 210 may generate and send commands to the schedule manager 212 based on user input provided to the GUI 210. The schedule manager 212 may generate and send output data on planning to the scheduler GUI 210 for review by the user 228.

[0072] The scheduler GUI 210 allows a mission planner user 228 to manually start and stop a planning session. The scheduler GUI 210 also allows the mission planner 228 to view a schedule on a timeline and a map and to zoom in and out to explore scheduled acquisitions and their associated acquisition requests.

[0073] The schedule manager 212 sends and receives data to and from the centralized ordering system 204 and the downstream missions 206.

[0074] Within the MMPS 202, the schedule manager 212 also communicates (e.g., sending and receiving data) with the area of interest (AOI) coverage planner 214, the opportunity generator 216, the acquisition order database 218, the acquisition request data service 220, the sensor service 222, the acquisition schedule data service 224, and the acquisition schedule optimizer 226.

[0075] The schedule manager 212 is the MMPS workflow manager. All external messages go through the schedule manager 212 (e.g., to and from ordering system 204, downstream missions 206).

[0076] The schedule manager 212 is configured to: ingest and collect acquisition orders; initiate pre-processing of the received acquisition orders; get possible imaging opportunities; direct the generation of AOI coverage plan(s); store acquisition requests in an acquisition request database (acquisition request data service 220 provides access to the acquisition request database); decide when new schedules need to be generated; determine the schedule horizon; start the schedule optimizer 226, following the starting and stopping criteria; and handle rejections of scheduled acquisitions.

[0077] The acquisition order database 218 stores the acquisition orders received from the ordering system 204.

[0078] The opportunity generator 216 is configured to generate imaging opportunities for a given acquisition request. The imaging opportunities cover the request’s AOI within the request’s period of interest using the admissible satellites and beam modes.

[0079] The AOI coverage planner 214 is configured to generate coverage plans for acquisition orders. For the AOI and the set possible imaging opportunities, one or more(configurable number) coverage plans are constructed by the AOI coverage planner 214. Each AOI coverage plan covers the entire AOI or a large portion of the AOI. The coverage percentage may be configurable (e.g., in the scheduler GUI 210).

[0080] The AOI Coverage Planner 214 is configured to generate AOI coverage plans and generate a set of strips from the set of opportunities.

[0081] The acquisition request data service 220 puts and receives acquisition requests to and from the acquisition request database.

[0082] The sensor service 222 retrieves mission and satellite configurations needed for planning and scheduling. Each configuration includes the satellite-specific constraints and parameters.

[0083] The acquisition schedule data service 224 puts and retrieves acquisition schedules to and from an acquisition schedule database. The acquisition schedule data service 224 provides access to the acquisition schedule database.

[0084] The acquisition schedule optimizer 226 is configured to generate optimized de-conflicted multi-mission acquisition schedules for the multiple satellite constellations. The acquisition schedule optimizer 226 generates one schedule for each satellite. The optimization criteria guide the schedule generation. The schedules serve the acquisition orders, as many as possible, and adhere to the resource constraints of the satellites. An order may be divided and scheduled to multiple satellites, and thus distributed to a plurality of (e.g., several) missions.

[0085] The acquisition schedule optimizer 226 is configured to generate schedules for fast-tasking scenarios (e.g., arrival and handling of an ad-hoc or an interrupt task of high priority that has to be scheduled immediately) and routine planning scenarios (e.g., short-term scheduling (several hours to a day) and medium-term scheduling (several days to a week)).

[0086] The acquisition schedule optimizer 226 is shown in further detail in Figure 3.

[0087] The acquisition schedule optimizer 226 includes one or more preprocessing modules, one or more post-processing modules, one or more greedy heuristicalgorithms, one or more improvement heuristic algorithms, and one or more exact optimization algorithms and models. Each algorithm generates a multi-mission schedule, a set of de-conflicted optimized schedules, one per satellite. In an embodiment, the system can be configured to use one algorithm for a fast-tasking scenario and to use another algorithm for a routine planning scenario.

[0088] For a received request (from centralized ordering system 204), a set of imaging opportunities is generated (in opportunity generator 216). From those imaging opportunities, the AOI coverage plans are created (in AOI coverage planner 214). AOI coverage planner 214 also generates strips and split opportunities.

[0089] When the time comes for a planning session to start, acquisition schedule optimizer 226 generates the multi-mission schedules, such as depicted in Figures 4 and 5.

[0090] Referring now to Figure 4, shown therein is a method 400 of generating an acquisition schedule, according to an embodiment. The method 400 may be implemented by the computer system 122 of Figure 1 or the system 200 of Figure 2.

[0091] At 402, the method 400 obtains a schedule generation trigger. The trigger may be a time or arrival of a high priority of fast-tasking acquisition request. Receipt of the trigger at 402 initiates schedule generation.

[0092] At 404, the method 400 includes filtering opportunities. This may include selecting opportunities that are within a planning (scheduling) horizon covering the requested AOI within the request time window (or period of interest).

[0093] At 406, the method 400 obtains a request. The request may be defined by an AOI and set of coverage plans. Each of the coverage plans may have a set of imaging strips, and each imaging strip may have a set of imaging opportunities.

[0094] At 408, the method 400 includes dividing opportunities. This may include, for any pair of imaging strips which belong to different acquisition requests, and which overlap in time and space, dividing these corresponding imaging opportunities. This results in an increased number of imaging opportunities but will allow increased reusability or imaging more by reducing the size of the opportunities that are in conflict.

[0095] At 410, the method 400 obtains a request. The request may include an AOI and a set of coverage plans, each with a set of imaging strips, and each strip with a set of imaging opportunities.

[0096] At 412, the method 400 includes generating a de-conflicted multi-mission optimized schedule. This may include evaluating a large number of de-conflicted schedules. This may include generating close-to-optimal, or sometimes optimal, schedules, by exploring explicitly or implicitly a very large number of different assignments, sequences, and schedules. There is one schedule for each satellite. The schedule includes the set of scheduled imaging opportunities that are also called the imaging activities of the satellite. Each order (request) may be satisfied by the imaging opportunities scheduled on more than one satellite and more than one mission.

[0097] At 414, the method 400 obtains an imaging activity. The imaging activity may be defined by a start time, and end time, a sensor, a mode, and a pointing spec.

[0098] Referring now to Figure 5, shown therein is a method 500 of generating multi-mission de-conflicted optimized schedules, according to an embodiment. The method 500 may be implemented by the computer system 122 of Figure 1 or the system 200 of Figure 2. In particular, the method 500 may be encoded as computer-executable instructions and implemented by the acquisition scheduling optimizer 226 of Figures 2 and 3.

[0099] At 502, the method 500 starts with acquisition requests, AOI coverage plans, strips, imaging opportunities, and split imaging opportunities. Such inputs are generated by other components of MMPS 202, as described herein.

[0100] At 504, the method 500 obtains an imaging opportunity. The imaging opportunity may be defined by a start time, an end time, and a sensor.

[0101] At 506, the method 500 includes preprocessing on the received inputs from 502. The preprocessing may be performed by preprocessing modules 302. Preprocessing may include adding start padding and of the gap to the start of each opportunity and adding end padding and of the gap to the end of each opportunity.

[0102] At 508, the method 500 obtains an imaging opportunity with paddings and gaps. The imaging opportunity may be defined by a start time, and end time, and a sensor.

[0103] At 510, the method 500 includes generating deconflicted optimized schedule(s) by applying one or more of the optimization algorithms. The optimization algorithms may include, for example, a greedy construction heuristic, a local search algorithm, a tabu search algorithm, a variable neighborhood search algorithm, and / or an exact optimization algorithm. Performance of operation 508 may include execution of one or more of components 304, 306, 308 of Figure 3.

[0104] At 512, the method 500 obtains a scheduled opportunity. The scheduled opportunity may be defined by a start time, an end time, a sensor, a mode, and a pointing spec.

[0105] At 514, the method 500 includes postprocessing on the scheduled opportunity. The postprocessing may include removing the start padding and of the gap from the start of each scheduled opportunity. The postprocessing may further include removing the end padding and of the gap from the end of each scheduled opportunity. The postprocessing may further include checking continuous imaging activities and introducing additional gap when the maximal imaging activity constraint is validated.

[0106] At 516, the method 500 obtains an imaging activity. The imaging activity may be defined by a start time, an end time, a sensor, a mode, and a pointing spec. The imaging activity is used to: (1 ) generate a spacecraft control schedule to be sent to satellite 106, or (2) generate an order to be sent to the ground segment (802) of a downstream satellite mission.

[0107] Referring now to Figure 6, shown therein is a method 600 of generating an AOI coverage plan, according to an embodiment. The method 600 may be implemented by the computer system 122 of Figure 1 or the system 200 of Figure 2. In particular, the method 600 may be encoded as computer-executable instructions and implemented by the AOI coverage planner 214 of Figure 2.

[0108] At 602, the method 600 starts with an acquisition request being received. In an embodiment, the arrival of each acquisition request triggers coverage plan generation.

[0109] At 604, the method 600 obtains an acquisition request. The acquisition request may be defined by an AOI, a time range, a geometry, a mode, and a sensor.

[0110] At 606, the method 600 includes calculating imagining opportunities (in 216) using the acquisition request. This may include calculating all of the imaging opportunities for AOIs by all allowable sensors for the configured planning horizon. Each imaging opportunity may be assigned a score.

[0111] At 608, the method 600 obtains an imaging opportunity. The imaging opportunity may be defined by a start time, an end time, and sensor.

[0112] At 610, the method 600 includes generating imaging strips for the imaging opportunities. This may include collapsing the time based imaging opportunities to a smaller set of geographically defined strips (geographic footprints). Each strip may be imaged by one or more imaging opportunities. Each strip may be assigned a score.

[0113] At 612, the method 600 obtains an imaging strip. The imaging strip may be defined by geographic area that may be covered by an imaging opportunity (one satellite pass).

[0114] At 614, the method 600 includes generating a coverage plan using the imaging strips. This may include, for each imaging request, a set of strips that cover the AOI. Each coverage plan may be assigned a score. The scores for a given acquisition request may be used to generate a ranking.

[0115] At 616, the method 600 obtains a coverage plan. The coverage plan may be defined by the set of strips covering the AOI .

[0116] The stored set of coverage plans from 616 may be an intermediate product (imaging opportunities and imaging strips). The intermediate product may then be used as input to acquisition schedule generation (e.g., by acquisition schedule optimizer 226 of Figure 2).

[0117] While the above description provides examples of one or more apparatus, methods, or systems, it will be appreciated that other apparatus, methods, or systems may be within the scope of the claims as interpreted by one of skill in the art.

Claims

Claims:1 . A method of automated multi-mission planning of satellite imagery acquisition, the method comprising: storing a list of admissible satellites and beam modes; receiving an image acquisition request that includes a requested area of interest (“AOI”) and a requested period of interest or time range; generating a set of imaging opportunities from the image acquisition request, wherein each imaging opportunity specifies a start time, and end time, and a sensor, wherein the set of imaging opportunities cover the requested AOI within the request period of interest using the admissible satellites and beam modes; generating at least one AOI coverage plan using the acquisition request and the set of imaging opportunities, wherein the at least one AOI coverage plan includes a set of imaging strips covering the requested AOI and the set of imaging opportunities for the requested AOI, wherein each imaging strip corresponds to a portion of a satellite swath of an admissible satellite that intersects with the requested AOI, and wherein each imaging strip specifies an area, a spec, and a sensor; providing (i) the image acquisition request and at least one coverage plan, and (ii) a set of satellites and satellite missions and their availability, to an acquisition schedule optimizer; and generating, via the acquisition schedule optimizer, a set of deconflicted acquisition schedules including one schedule for each available satellite, using one or more optimization algorithms.

2. The method of claim 1 , wherein the image acquisition request further specifies a geometry, a mode, and a sensor.

3. The method of claim 1 , wherein the requested AOI is characterized by one or more of: a request priority specifying a priority of the user and importance of the task; a satellite or sensor, potentially with preference values; a resolution, mode, and polarization, potentially with preference values; a range of incidence angles; one or more look directions, the look directions being left-looking or right-looking; a pass direction indicating an ascending pass (from South to North) and / or a descending pass (from North to South); and repeated imaging or a standing order (e.g., daily, weekly repeat cycle).

4. The method of claim 1 , wherein each imaging opportunity further specifies a satellite, an orbit, the image acquisition request, a strip, and an area of the strip.

5. The method of claim 1 , wherein each imaging opportunity includes: a time window; an associated satellite, orbit, mode, and geometry (e.g., incidence angle); an associated imaging strip and request; observation (imaging) duration for the imaging strip associated with the imaging opportunity with the associated satellite, mode, and geometry; quality of imaging including how well the imaging opportunity on the satellite satisfies the requirements of the image acquisition request.

6. The method of claim 1 , wherein the AOI coverage plan covers all of the requested AOI.

7. The method of claim 1 , wherein the AOI coverage plan covers a portion of the requested AOI that meets a coverage threshold that is less than 100%.

8. The method of claim 7, wherein the coverage threshold is configured by a user through a graphical user interface.

9. The method of claim 1 , wherein the at least one AOI coverage plan is a plurality of AOI coverage plans, and wherein the method further includes assigning a score to each of the plurality of AOI coverage plans and ranking the plurality of AOI coverage plans for the image acquisition request according to the assigned scores.

10. The method of claim 1 , further comprising dividing each schedule in the set of acquisition schedules into separate orders and, for each satellite mission, submitting the separate orders to a planning system of that satellite mission.

11. The method of claim 1 , further comprising receiving an acquisition order from a centralized ordering system and translating one or more tasks in the acquisition order into the image acquisition request.

12. The method of claim 11 , wherein the acquisition order defines a type of imagery, a time, a location, and a collecting source.

13. The method of claim 1 , wherein the AOI coverage plan includes plan quality data indicating how well the AOI coverage plan satisfies the image acquisition request, and wherein the plan quality data includes one or more of a measure of how compatible selected satellites are for the image acquisition request, how much of the AOI is covered by the AOI coverage plan, and how much overlap there is among the set of imaging strips.

14. The method of claim 1 , wherein the one or more optimization algorithms include one or more greedy heuristic algorithms, one or more improvement heuristic algorithms, and one or more exact optimization algorithms.

15. The method of claim 1 , further comprising using a first of the one or more optimization algorithms for a fast-tasking scenario and a second of the one of more optimization algorithms for a routine planning scenario.

16. The method of claim 1 , wherein the one or more optimization algorithms include one or more of: a greedy construction heuristic, a local search algorithm, a tabu search algorithm, a variable neighborhood search algorithm, and an exact optimization algorithm.

17. The method of claim 1 , wherein for each satellite the acquisition schedule includes: a list of opportunities each with a start time and end time of the observation (imaging) of the associated strip; and the maneuver time and activity including starting pointing location and ending pointing location of the camera / sensor.

18. The method of claim 1 , further comprising generating a spacecraft control schedule based on the set of deconflicted acquisition schedules and sending the spacecraft control schedule to the satellite.

19. The method of claim 1 , further comprising generating an order based on the set of deconflicted acquisition schedules and sending the order to a ground segment of a downstream satellite mission.

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