JP2022188857A - Satellite monitoring device, satellite monitoring method, and program - Google Patents

Abstract

To provide a satellite monitoring device which makes it possible to efficiently monitor multiple satellites.SOLUTION: There is provided a satellite monitoring device including: a reception processing unit for receiving a plurality of first data groups which are output from a plurality of satellites and each expressed in a unique format corresponding to each of the plurality of satellites; a conversion processing unit for converting the plurality of first data groups which are received and each expressed in the unique format into a plurality of second data groups which are each expressed in a standard format and each corresponding to each of the plurality of satellites; a display processing unit for displaying the plurality of second data groups after conversion on a screen; and a determination processing unit for determining the state of each of the plurality of satellites on the basis of the plurality of second data groups.SELECTED DRAWING: Figure 4

Description

The present invention relates to a satellite monitoring device, a satellite monitoring method, and a program.

Currently, there are about 6,000 artificial satellites orbiting the earth, and the number is expected to increase further in the future. In addition, a large number of specialized operators monitor 24 hours a day, 365 days a year to see if these many artificial satellites are operating normally. Patent Literature 1 discloses a satellite monitoring and control system that monitors a plurality of satellites.

JP 2016-116147 A

Since the vast amount of data output from the sensors mounted on many satellites orbiting the earth is not standardized in particular, the data obtained and the data format differ from satellite to satellite, and each data indicates They also have different meanings. Therefore, the current situation is that the monitoring of artificial satellites relies on the experience of operators. Considering that the number of sensors installed on satellites is expected to increase in the future, and that the number of satellites orbiting the earth is expected to increase further, it is important to monitor satellites efficiently. is considered to be necessary.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a satellite monitoring apparatus capable of efficiently monitoring a large number of satellites.

A satellite monitoring apparatus according to an aspect of the present invention includes a reception process for receiving a plurality of first data groups output from a plurality of satellites and expressed in a format unique to each of the plurality of satellites. and conversion processing for converting the plurality of first data groups expressed in the received unique format into a plurality of second data groups corresponding to each of the plurality of satellites expressed in a standard format. a display processing unit that displays the converted plurality of second data groups on a screen; and a determination processing unit that determines the state of each of the plurality of artificial satellites based on the plurality of second data groups. , has

ADVANTAGE OF THE INVENTION According to this invention, the artificial satellite monitoring apparatus which can monitor many artificial satellites efficiently can be provided.

It is a figure which shows the structural example of the artificial satellite monitoring system which concerns on this embodiment. FIG. 10 is a diagram showing an example of a missing pattern; It is a figure which shows the hardware structural example of an artificial satellite monitoring apparatus. It is a figure which shows the functional block structural example of an artificial satellite monitoring apparatus. It is a flowchart which shows an example of the processing procedure which an artificial satellite monitoring apparatus performs. FIG. 11 is a diagram showing a display example when second data of the same type are aggregated and displayed; FIG. 10 is a diagram showing a display example when the same type of second data is displayed side by side; FIG. 10 is a diagram showing screen display examples when outlier removal is not performed and when outlier removal is performed; It is a figure for demonstrating the problem in performing the graph display of 2nd data, and a solution. FIG. 4 is a diagram for explaining downsampling processing;

Embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that, in each figure, the same reference numerals have the same or similar configurations.

<System configuration>
FIG. 1 is a diagram showing a configuration example of an artificial satellite monitoring system 1 according to this embodiment. The satellite monitoring system 1 includes a satellite monitoring device 10, a terminal 20 connected to the satellite monitoring device 10, one or more satellites 30 to be monitored, and receiving signals transmitted from the satellites 30. and one or more customer devices 50 that collect signals transmitted from the satellites 30 via the antennas 40 .

The artificial satellite 30 has many sensors and transmits data measured by each sensor. Data transmitted from the artificial satellite 30 is received by an antenna 40 installed on the ground and transmitted to the customer device 50 . The artificial satellite 30 includes devices such as optical sensors, radar sensors, and other devices (called “mission devices” or “mission units”) necessary for carrying out the missions imposed on the artificial satellite 30, and the satellite operates. It includes the basic functions (called "bus equipment" or "bus section") necessary to continue to operate. The bus unit includes, for example, an antenna for transmitting and receiving data to and from the ground, a radio device, a data recorder, a star sensor for controlling the attitude of the artificial satellite 30, an inertial reference device, a reaction wheel, a solar cell, a battery, an attitude It includes rocket thrusters and propellant tanks used for control and orbit correction.

The customer device 50 is managed by an organization that operates the satellite 30, and monitors and controls the satellite 30 owned by the organization. The customer device 50 receives various data transmitted from the mission unit and the bus unit of the artificial satellite 30, and analyzes the received various data. In the present embodiment, it is assumed that there are multiple organizations operating the satellites 30, and the satellite monitoring device 10 collectively monitors the satellites 30 operated by the multiple organizations. there is

The satellite monitoring device 10 is connected to each customer device 50 and acquires various data transmitted from the satellite 30 via the customer device 50 . In addition, the satellite monitoring device 10 collectively displays a large number of collected data and analyzes various data to monitor whether each satellite 30 is operating normally. ” will be realized. The terminal 20 connected to the satellite monitoring device 10 may be located in an organization that manages the customer device 50 . In other words, an operator (also referred to as a user) of an organization that operates the satellite 30 may be able to refer to the screen of the satellite monitoring device 10 while staying in each organization.

Currently, the health monitoring of the artificial satellite 30 is manually performed by an operator in each organization using the customer device 50 . Health monitoring is mainly performed by an operator monitoring and analyzing various data output from the bus unit. However, since the artificial satellite 30 exists in the harsh environment of outer space, the data received from the artificial satellite 30 has many defects and errors. Since the data output by the mission unit is important data for carrying out the mission, it is received by all antennas 40 on the earth in order to avoid loss as much as possible. In many cases, this data is treated as having a lower importance than the data of , and there is also an operation in which it is acquired only during the period during which it can be received by the antenna 40 in Japan (the period during which it is visible). In this case, as shown in A of FIG. 2, all the data will be lost during the period in which the antenna 40 cannot receive the radio wave from the artificial satellite 30 (invisible period). Even when the antenna 40 can receive data from the artificial satellite 30, in order to keep the data of the mission part within the communication band, the reception cycle is set for the data of the bus part. An operation of deleting data (that is, intentionally missing data) is also performed. In this case, as shown in FIG. 2B, only part of the data is missing. Therefore, it is difficult to say that the various data output from the bus unit used for soundness monitoring are clean data with many defects compared to the data output from the mission unit.

As described above, the monitoring of the artificial satellite 30 is performed based on a huge amount of data with many defects and errors, and currently relies on the experience and intuition of the operator. The customer device 50 also has a function to detect changes in data and output an alarm. There is also the problem of In addition, since anomaly detection is performed according to a predetermined logic, it is difficult to cope with deterioration of equipment mounted on the satellite 30 and environmental changes, and it is also difficult to deal with unknown anomalies.

Therefore, the satellite monitoring device 10 according to the present embodiment can centrally handle the data of each satellite 30 acquired from each customer device 50, and utilizes machine learning or the like to improve the operator's monitoring know-how. systematization makes it possible to monitor the artificial satellite 30 more efficiently. Although the satellite monitoring device 10 acquires the data of the satellite 30 via the customer device 50, this embodiment is not limited to this. A system configuration in which data is obtained directly from the antenna 40 without going through the customer device 50 is also possible.

<Hardware configuration>
FIG. 3 is a diagram showing a hardware configuration example of the satellite monitoring device 10. As shown in FIG. The satellite monitoring device 10 includes a processor 11 such as a CPU (Central Processing Unit) or a GPU (Graphical Processing Unit), a memory, a storage device 12 such as a HDD (Hard Disk Drive) and/or an SSD (Solid State Drive), a wired or It has a communication IF (Interface) 13 for wireless communication, an input device 14 for receiving input operations, and an output device 15 for outputting information. The input device 14 is, for example, a keyboard, touch panel, mouse and/or microphone. The output device 15 is, for example, a display, touch panel and/or speaker.

The satellite monitoring device 10 may be composed of one or a plurality of physical servers or the like, or may be composed of a virtual server that operates on a hypervisor, or may be composed of a cloud server. It may be configured using a server. When configured with a plurality of servers or the like, the satellite monitoring device 10 may be called a satellite monitoring system.

<Functional block configuration>
FIG. 4 is a diagram showing a functional block configuration example of the satellite monitoring device 10. As shown in FIG. The satellite monitoring device 10 includes a reception processing unit 101 , a conversion processing unit 102 , a display processing unit 103 , a determination processing unit 104 and a storage unit 105 . The reception processing unit 101, the conversion processing unit 102, the display processing unit 103, and the determination processing unit 104 are implemented by the processor 11 of the satellite monitoring device 10 executing a program stored in the storage device 12. be able to. Also, the storage unit 105 can be implemented using the storage device 12 included in the satellite monitoring device 10 . Also, the program can be stored in a storage medium. The storage medium storing the program may be a non-transitory computer readable medium. The non-temporary storage medium is not particularly limited, but may be a storage medium such as a USB memory or CD-ROM, for example.

The reception processing unit 101 receives a plurality of first data groups expressed in formats specific to each of the plurality of satellites 30, which are output from sensors mounted on the plurality of satellites 30. FIG.

In this embodiment, the “first data group” means a plurality of time-series data expressed in a unique format output from one artificial satellite 30 . "First data" means one piece of time-series data output from one artificial satellite 30 and expressed in a unique format. That is, the first data is one of the multiple pieces of time-series data included in the first data group. In addition, in this embodiment, "time-series data" may be simply referred to as "data".

Also, the reception processing unit 101 receives a plurality of first data groups from a plurality of customer devices 50 . The reception processing unit 101 also stores the received plurality of first data groups in the first data DB 105a.

The conversion processing unit 102 extracts from the first data DB 105a the plurality of first data groups expressed in the format unique to the satellite 30 received by the reception processing unit 101, and converts the plurality of satellites expressed in the standard format. into a plurality of second data groups corresponding to each of The reception processing unit 101 also stores the second data group converted into the standard format in the second data DB 105b.

In this embodiment, the "second data group" means a data group after being converted into a standard format based on the first data group. Also, "second data" means data after being converted into a standard format based on the first data. note that. The "second data" may be called variables.

The display processing unit 103 displays the plurality of second data groups converted by the conversion processing unit 102 on the screen. The plurality of second data groups contain a large amount of second data and are recorded for a long period of time. Therefore, even if the second data group is displayed on one screen, each second data is collapsed and displayed, making it difficult for the operator to recognize the data. Therefore, the display processing unit 103 has a function of thinning out and displaying the second data of the same type, a function of scaling and displaying the second data while maintaining the outline of the second data, and the like.

The determination processing unit 104 determines the state of each of the plurality of artificial satellites based on the plurality of second data groups stored in the second data DB 105b. The determination processing unit 104 detects abnormal data from the second data group using, for example, a trained model having the ability to detect abnormal second data, thereby causing the satellite 30 to It may be determined whether or not a failure has occurred. Further, the determination processing unit 104 may relearn the trained model based on the tag or the like attached to the second data by the operator who referred to the second data.

The storage unit 105 stores a first data DB 105a, a second data DB 105b, and an annotation DB 105c that stores tags given to the second data by the operator who referred to the second data of the artificial satellite 30. FIG.

<Processing procedure>
FIG. 5 is a flowchart showing an example of a processing procedure performed by the satellite monitoring device 10. As shown in FIG.

The reception processing unit 101 receives, from each customer device 50 , a plurality of first data groups expressed in a unique format corresponding to each of the plurality of artificial satellites 30 . The first data includes measured values measured by the sensors mounted on the satellites 30 and/or predefined state values (for example, "0" is OFF, "1" is ON, etc.).

The reception processing unit 101 also stores the received first data group in the first data DB 105a. When storing the received first data group in the first data DB 105a, the reception processing unit 101 stores an identifier that can uniquely identify the first data group (hereinafter referred to as a "first identifier") as the first data group. It may be stored in the first data DB 105a in association with the group. For example, when the reception processing unit 101 receives 100 first data groups (that is, receives data from 100 satellites 30), each first data group is given a different first identifier. Stored in the first data DB 105a. The first identifier may be, for example, an identifier that can uniquely identify the artificial satellite 30 . The number of time-series data included in each first data group may be different.

In addition, the reception processing unit 101 receives from each customer device 50 information other than the plurality of first data groups that can be used when the satellite monitoring device 10 performs data conversion processing, data display processing, and data determination processing (hereinafter referred to as , referred to as “first additional information”). The first additional information includes, for example, data definition information related to mission unit data and/or bus unit data, operation records of the satellite 30 created by the operator who monitors the satellite 30, and data related to the space environment. It may be

In step S20, conversion processing unit 102 extracts a plurality of first data groups from first data DB 105a and converts the extracted plurality of first data groups into a standard format. The conversion processing unit 102 also stores a plurality of second data groups generated by converting into the standard format in the second data DB 105b.

Here, for each first data group, the satellite monitoring device 10 stores in the storage unit 105 "conversion definition information" that defines a method for converting each first data included in the first data group into a standard format. It may be left as is. The definition file may be stored in storage unit 105 in association with a first identifier that can uniquely identify the first data group. For example, the conversion processing unit 102 acquires a first data group to be converted into a standard format and a first identifier from the first data DB 105a, and stores conversion definition information associated with the acquired first identifier from the storage unit 105. may be obtained. Further, the conversion processing unit 102 may convert the first data group into the standard format based on the acquired conversion definition information to generate the second data group. Like the first data, the second data also includes measured values measured by the sensors mounted on the artificial satellite 30 and/or values indicating predefined states. However, the measured values and the like included in the second data are not necessarily the same values as the first data, and may be replaced with other values according to the definition of the standard format.

The transformation definition information includes all information necessary to transform the first data into the standard format. For example, when the first data is text data, the conversion definition information may define the delimiter of each data in the text data, the meaning of each data, the character code used, and the like. Further, when the first data is binary data, the format definition of the binary data, the meaning of each data, and the like may be defined.

Although there are no restrictions on the conversion processing performed by the conversion processing unit 102, for example, processing to convert binary data to text data (or vice versa), processing to change the scale of data, and conversion of data values to values defined in a standard format. , processing to generate or interpolate one or more new second data from one or more first data (for example, generation of summary data, new generation of second data, etc.) may be included. For example, the conversion processing unit 102 generates new second data by calculating one or a plurality of second data selected from a plurality of second data groups based on predetermined calculation definition information. can be The predetermined operation definition information may be part of the conversion definition information, or may be defined separately from the conversion definition information. By generating new second data that is not included in the first data, the operator can monitor the satellite 30 more efficiently than referring to the first data as it is. become.

Further, the conversion processing unit 102 may perform processing for repairing missing data and removing outliers in addition to processing for conversion to the standard format. For example, the conversion processing unit 102 may detect outliers included in the plurality of second data groups by analyzing the plurality of second data groups, and delete the detected outliers. Any algorithm may be used to remove outliers, for example, k nearest neighbor method, local outlier factor method (Lof method), One Class SVM (Support Vector Machine) and FFT (Fast Fourier Transform) filter etc. may be used. Alternatively, a percentile method may be used to regard values that do not fall within a predetermined percentile (for example, the 99th percentile) in each second data as outliers. This makes it possible to eliminate the adverse effects of the outliers in the display processing and determination processing of the second data, which will be described later.

Further, the conversion processing unit 102 converts the first additional information received by the reception processing unit 101 into information in a standard format (hereinafter referred to as "second additional information") recognizable by the satellite monitoring device 10. It may be converted. In this case, the conversion definition information may include all information necessary for converting the first additional information into the second additional information.

In step S30, the display processing unit 103 displays the plurality of second data groups converted by the conversion processing unit 102 on the screen. At this time, the display processing unit 103 may use at least part of the second additional information to display the second data group on the screen. Further, the display processing unit 103 analyzes the second data group corresponding to the designated satellite 30 to classify the plurality of second data included in the second data group into an arbitrary number of types, The second data classified according to each type may be displayed on the screen of the terminal 20 by arranging them by type. Further, the display processing unit 103 may select at least one second data for each type from the classified second data for each type and display it on the screen of the terminal 20 . The type of data may be classified based on the global and/or local similarity of the time-series data forming the second data. Any method can be used to classify the second data by type. -Method combining the medoids method" and "spectral clustering", etc.) may be used for classification.

FIG. 6 is a diagram showing a display example when the second data of the same type are collectively displayed. FIG. 6A shows, for example, a display example when 381 pieces of second data output from a designated artificial satellite 30 are arranged in order of type and displayed graphically on one screen. By arranging hundreds of pieces of second data in order of degree of similarity and displaying them side by side in the vertical direction in this way, the operator can perceive the movement of hundreds of pieces of second data as one pattern, which is unusual for normal operation. can easily recognize that different states exist.

FIG. 6B classifies the 381 pieces of second data that are similar in shape when graph-displayed (that is, that the behavior of the data is similar) as second data of the same type, and further 3 shows an example in which 381 pieces of second data are aggregated into 32 pieces and displayed by selecting one piece of second data to be displayed from a plurality of pieces of second data of the same type. Similarly, FIG. 6C shows an example in which 32 pieces of second data are subjected to the same processing as described above, and the 32 pieces of second data are aggregated into 8 pieces and displayed. In B of FIG. 6, the shape of the second data can be grasped to some extent as compared with A in FIG. Furthermore, in C of FIG. 6, the shape of the second data can be grasped at a glance as compared with B in FIG. By aggregating and displaying the second data having similar behaviors in this manner, the operator can easily understand the operating state of the artificial satellite 30 .

Further, the display processing unit 103 may extract a plurality of second data belonging to a specified type from among the plurality of second data classified for each type and display them on the screen of the terminal 20. .

FIG. 7A shows an example in which nine pieces of second data belonging to the same type are displayed side by side, and FIG. 7B shows an example in which five pieces of second data belonging to another same type are displayed side by side. An example case is shown. By displaying a plurality of pieces of second data having similar behavior side by side in this way, the operator can compare the outputs of the plurality of sensors belonging to the same type in more detail. In addition, the operator can comprehend minute differences between the second data by comparing the outputs of the plurality of sensors in more detail.

As described above, the conversion processing unit 102 may remove outliers when converting to the standard format. FIG. 8 is a diagram showing screen display examples when outlier removal is not performed and when outlier removal is performed. FIG. 8A shows an example of graph display of the second data with outliers remaining, and FIG. 8B shows an example of graph display of the second data with the outliers removed. . As shown in FIG. 8, by removing the outliers, the vertical margins of the graph are reduced and the shape of the graph becomes clearer. be able to comprehend. The display control unit 103 may display the second data after removing the outliers in the display examples of FIGS. 6 and 7 as well.

Further, the display processing unit 103 maintains the display shape of the graph of the second data when displaying the designated second data contained in the second data group corresponding to the designated satellite on the screen of the terminal 20. Enlarging and reducing display may be performed as they are.

FIG. 9 is a diagram for explaining problems and solutions when displaying the second data in a graph. Consider a case where a square frame W10 (for example, a predetermined month) in the graph of the second data shown in A of FIG. 9 is enlarged and displayed. Here, the second data is data collected in a short period such as one minute period, and even if one month's worth of data is enlarged and displayed, the amount of data is enormous. Further, in the present embodiment, the display processing unit 103 reduces the number of data by down-sampling the second data, and draws the down-sampled second data in order to reduce the processing load when drawing the graph. shall be

At this time, if the second data is simply down-sampled and displayed, a waveform different from the original waveform may be displayed as shown in 7B. Therefore, the display processing unit 103 performs enlargement and reduction display while maintaining the display shape of the graph of the second data. For example, in order to display the second data while maintaining the appearance of the original waveform, the display processing unit 103 extracts the maximum and minimum values of the second data at predetermined sampling intervals, and combines the extracted values to display the second data. 2 data may be drawn. More specifically, for the second data to be displayed, the display processing unit 103 obtains the maximum value of the second data at a predetermined sampling period (Δt), and further obtains the maximum value of the second data at a sampling period (Δt) shifted by Δt/2. to obtain the minimum value of the second data, and draw a graph by connecting the obtained maximum and minimum values in order.

FIG. 10 is a diagram for explaining the downsampling process. In FIG. 10, it is assumed that the interval between two adjacent times among times T1 to T10 is Δt/2. For the second data G, the display processing unit 103 acquires the maximum value of the second data at a predetermined sampling period (Δt) with T1 as the start time. That is, the display processing unit 103 acquires the maximum value of the second data at times T1 to T3, T3 to T5, T5 to T7, and T7 to T9, as shown in A of FIG. Similarly, for the second data G, the display processing unit 103 obtains the minimum value of the second data G at a predetermined sampling period (Δt) with a start time of T2, which is the time Δt/2 after the time T1. That is, the display processing unit 103 acquires the minimum value of the second data at times T2 to T4, T4 to T6, T6 to T8, and T8 to T10. Subsequently, as shown in FIG. 10B, the display processing unit 103 plots the maximum value acquired in the sampling period (Δt) at the center time of each sampling period (that is, the maximum value M1 at times T1 to T3 is , plotted at time T2), and the minimum value obtained in the sampling period (Δt) is plotted at the center time of each sampling period (that is, the minimum value S1 from time T2 to T4 is plotted at time T3). Subsequently, the display control unit 103 draws a graph of the down-sampled second data by connecting the plotted points with line segments in chronological order (dotted line H in B of FIG. 10). As a result, even when the second data is enlarged and displayed on the screen of the terminal 20, the shape of the waveform is maintained, so that the operator can grasp the state of the satellite 30 more accurately. Become. Further, when the operator performs an operation to enlarge or reduce the range in which the second data is displayed on the screen of the terminal 20 by mouse operation, touch operation, or the like, the shape of the waveform of the second data changes. By doing so, it is possible to suppress the problem of not knowing which range has been enlarged or reduced.

In addition, the display processing unit 103 receives an input of a tag from the operator for the second data included in the second data group specified by the operator among the plurality of second data groups, and stores the received tag in the annotation DB 105c. You may make it store. More specifically, the display processing unit 103 may accept, from the operator, specification of the second data to which the tag is attached, and specification of the contents of the tag to be attached and the time on the screen displaying the second data. good. Further, the display processing unit 103 may associate information indicating the second data input from the operator, information indicating the time, and the content of the attached tag, and store them in the annotation DB 105c. good.

The content of the tag may be any content, but may be, for example, the result of the operator's determination of the state of the artificial satellite 30 . For example, a tag such as "highly likely to be abnormal" or "highly likely to be normal" may be used.

Further, the display processing unit 103 extracts, from the second data group, second data exhibiting behavior similar to the second data tagged by the operator, and the extracted second data is also displayed by the operator. may be assigned the same tag as the tag assigned by . The second data showing similar behavior may be, for example, second data whose value indicating the degree of similarity to the tagged second data is equal to or greater than a predetermined value.

In addition, the display processing unit 103 classifies the plurality of second data using an unsupervised learning algorithm, displays the second data group in the classified unit on the screen of the terminal 20, and operates by referring to the screen. An input of a tag indicating the result of the operator's determination of the state of the artificial satellite 30 may be accepted from the operator. Further, the display processing unit 103 may store the tag input by the operator in the annotation DB 105c. This makes it possible to efficiently collect tags indicating the results of the operator's determination of the state of the satellite 30 .

In step S40, the determination processing unit 104 inputs each of the plurality of second data groups to a trained model having the ability to determine the state of the satellite 30, and based on the output result obtained by the plurality of satellites The status of each of satellites 30 is determined. The display processing unit 103 displays the state of each of the plurality of artificial satellites 30 determined by the determination processing unit 104 on the screen of the terminal 20 . The determination processing unit 40 may determine the state of each of the plurality of artificial satellites 30 using at least part of the second additional information.

In addition, the learned model is learned by using, for example, the second data tagged as "highly likely to be abnormal" or "highly likely to be normal" by the operator as training data. can be generated by For example, the determination processing unit 104 extracts, from the annotation DB 105c, the second data tagged by the operator as "highly likely to be abnormal" or "highly likely to be normal", A trained model is generated by generating a plurality of teacher data by extracting data in a predetermined range of times centered on the time when is assigned, and training the model with the generated multiple teacher data. can be

Further, the determination processing unit 104 may generate a trained model for each artificial satellite 30 or may generate a common trained model for each artificial satellite 30 .

In addition, the determination processing unit 104 generates additional teacher data from the tagged second data added to the annotation DB 105c after generating the teacher data for learning the trained model. The learning data may be used to additionally learn the trained model.

By having the model learn based on the tags given by the operator, it becomes possible to monitor the satellites 30 more accurately and without omissions, which conventionally relied on the experience and intuition of the operator. In addition, when a learned model common to each artificial satellite 30 is created, it becomes possible to expand monitoring know-how for a certain artificial satellite 30 to other artificial satellites 30 as well.

<Summary>
According to the embodiment described above, the satellite monitoring device 10 converts the data expressed in the unique format output from each satellite 30 into the standard format, and displays the data converted into the standard format on the screen. In addition, the state of each artificial satellite 30 is determined using the data. This allows efficient monitoring of a large number of satellites.

The embodiments described above are for facilitating understanding of the present invention, and are not intended to limit and interpret the present invention. Flowcharts, sequences, elements included in the embodiments, their arrangement, materials, conditions, shapes, sizes, and the like described in the embodiments are not limited to those illustrated and can be changed as appropriate. Also, it is possible to partially replace or combine the configurations shown in different embodiments.

DESCRIPTION OF SYMBOLS 1... Artificial satellite monitoring system 10... Artificial satellite monitoring apparatus 11... Processor 12... Storage device 13... Communication IF 14... Input device 15... Output device 20... Terminal 30... Artificial satellite 40... Antenna , 50... customer device, 101... reception processing unit, 102... conversion processing unit, 103... display processing unit, 104... determination processing unit, 105... storage unit, 105a... first data DB, 105b... second data DB, 105c …Annotation DB

Claims (9)

a reception processing unit that receives a plurality of first data groups output from a plurality of satellites and expressed in a format unique to each of the plurality of satellites;
a conversion processing unit that converts the plurality of first data groups expressed in the received unique format into a plurality of second data groups corresponding to each of the plurality of artificial satellites expressed in a standard format;
a display processing unit that displays the converted plurality of second data groups on a screen;
a determination processing unit that determines the state of each of the plurality of artificial satellites based on the plurality of second data groups;
A satellite monitoring device having a The conversion processing unit detects outliers contained in the plurality of second data groups by analyzing the plurality of second data groups, and deletes the detected outliers.
The satellite monitoring device according to claim 1. each of the plurality of second data groups includes a plurality of second data;
The conversion processing unit generates new second data by calculating one or a plurality of second data selected from the plurality of second data groups based on predetermined calculation definition information.
The artificial satellite monitoring device according to claim 1 or 2. The display processing unit analyzes the second data group corresponding to the designated satellite to classify the plurality of second data included in the second data group by type, and for each classified type selecting at least one second data for each type from the second data of and displaying it on the screen;
A satellite monitoring device according to any one of claims 1 to 3. The display processing unit, when displaying the specified second data included in the second data group corresponding to the specified artificial satellite, expands the display shape of the graph of the second data while maintaining the display shape. and zoom out,
A satellite monitoring device according to any one of claims 1 to 4. The display processing unit displays a predetermined tag specified by the user at a time specified by the user for the second data included in the second data group specified by the user among the plurality of second data groups. to give
A satellite monitoring device according to any one of claims 1 to 5. The determination processing unit, based on an output result obtained by inputting each of the plurality of second data groups into a trained model having the ability to determine the state of the satellite, determines the status of the plurality of satellites. The satellite monitoring device according to any one of claims 1 to 6, wherein each state is determined. A satellite monitoring method performed by a satellite monitoring device,
receiving a plurality of first data groups output from a plurality of satellites and expressed in a format unique to each of the plurality of satellites;
converting the plurality of first data groups expressed in the received unique format into a plurality of second data groups corresponding to each of the plurality of satellites expressed in a standard format;
displaying the converted plurality of second data groups on a screen;
determining the state of each of the plurality of artificial satellites based on the plurality of second data groups;
A satellite monitoring method comprising: receiving a plurality of first data groups output from a plurality of satellites and expressed in a format unique to each of the plurality of satellites;
converting the plurality of first data groups expressed in the received unique format into a plurality of second data groups corresponding to each of the plurality of satellites expressed in a standard format;
displaying the converted plurality of second data groups on a screen;
determining the state of each of the plurality of artificial satellites based on the plurality of second data groups;
A program that causes a computer to run

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