Environmental data observation planning support device and environmental data observation planning support method

Abstract

To plan an observation route with high observation value while satisfying transmission conditions such as upper limit number of observation data transmissions and upper limit amount of transmission data.SOLUTION: An environmental data observation planning support device 1 includes: an observation area determination unit 103 configured to determine an observation candidate area for an observation device based on observation route data; an observation value evaluation unit 104 configured to use environmental information data in the observation candidate area to evaluate an observation value of observation data at each position in the observation candidate area; an observation value correction unit 105 configured to correct the observation value of each position in the observation candidate area; and an observation data extraction position determination unit 106 configured to determine an extraction position for the observation data so that the observation value of the observation data to be transmitted is maximized according to transmission conditions of the observation data.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an environmental data observation plan formulation support device and an environmental data observation plan formulation support method.

Background Art

[0002] In order to accurately estimate the ocean environment, it is necessary to observe seawater temperature, salinity concentration, etc. One of the means for observing the ocean environment is an underwater glider. An underwater glider is an autonomous observation device that has a buoyancy control mechanism and can perform long-distance and long-term observations while repeatedly surfacing and sinking in water. The observation period by an underwater glider can reach several months in the case of a long period.

[0003] On the other hand, since the transmission of the observation data of the underwater glider is performed by satellite communication or acoustic communication, there are strong restrictions on the communication frequency and communication speed. Since seawater hardly passes radio waves, satellite communication can only be performed when the underwater glider surfaces and exists on the sea. Further, when the underwater glider is sinking in the deep sea, although it is possible to transmit the observation data using acoustic communication, ships and facilities that receive the communication data need to be arranged within a range of several kilometers in the horizontal distance from the position of the underwater glider, and the communication speed is also very slow. Therefore, it is necessary to formulate a plan to perform effective observations with less communication frequency and data capacity by extracting important data from the observation data and transmitting it. Thus, for example, a technique has been proposed in which an observation plan is calculated based on the importance of the observation data described in Patent Document 1, and an observation plan that covers the observation target area is performed with as few round trips as possible. Further, for example, a method has been proposed in which an observation position with high observation value is calculated using the sea surface water temperature time series data described in Non-Patent Document 1.

[0004] Patent Document 1 describes a technique in which, based on observation request information, observation scenes with high individual importance are extracted from an observation scene list, and a provisional observation plan combining the observation scenes is evaluated based on the extracted observation scene list and vehicle information, and a provisional observation plan with a high evaluation value is determined.

[0005] Non-Patent Document 1 describes a technique for applying proper orthogonal decomposition (POD) to time-series data of sea surface water temperature, evaluating observed values using a sensor candidate matrix arranged with the obtained spatial POD modes, and determining the observation point positions, and a technique for weighting the observed values by the observation cost and optimizing both the reduction of the observation cost and the observation positions.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Non-Patent Documents

[0007]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0008] As described above, in Patent Document 1, a technique has been proposed in which an observation plan is calculated based on the importance of observation data, and an observation plan is carried out to cover an observation target area with as few round trips as possible. However, the observation plan technique described in Patent Document 1 does not consider transmission conditions such as the number of times of transmitting observation data and the upper limit amount of transmitted data. Further, in Non-Patent Document 1, a method has been proposed for calculating an observation position having a high observation value using time series data of sea surface water temperature. However, the observation position calculation method described in Non-Patent Document 1 also does not consider the above-described transmission conditions of observation data.

[0009] The present invention has been made in view of the above circumstances, and an object of the present invention is to plan an observation route having a high observation value while satisfying transmission conditions such as the upper limit number of times of transmitting observation data and the upper limit amount of transmitted data.

Means for Solving the Problems

[0010] The present invention includes an observation area determination unit that determines an observation candidate area of an observation device based on observation route data, an observation value evaluation unit that evaluates the observation value of observation data at each position in the observation candidate area using environmental information data in the observation candidate area, an observation value correction unit that corrects the observation value of each position in the observation candidate area, and an observation data extraction position determination unit that determines an extraction position of observation data so that the observation value of the transmitted observation data becomes the highest according to the transmission conditions of the observation data.

Effects of the Invention

[0011] According to the present invention having the above configuration, it is possible to satisfy transmission conditions such as the upper limit number of times of transmitting observation data and the upper limit amount of transmitted data, and to plan an observation route having a high observation value. Problems, configurations, and effects other than the above will be clarified by the description of the following embodiments.

Brief Description of the Drawings

[0012]

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Best Mode for Carrying Out the Invention

[0013] Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same function or configuration are denoted by the same reference numerals, and redundant descriptions are omitted.

[0014] <First Embodiment> [Configuration Example of Environmental Data Observation Plan Formulation Support Device] First, the configuration of the environmental data observation plan formulation support device 1 according to the first embodiment of the present invention will be described. FIG. 1 is a block diagram showing a configuration example of the environmental data observation plan formulation support device 1 according to this embodiment. The environmental data observation plan formulation support device 1 is an example of a computer device, and as shown in FIG. 1, it includes a CPU (Central Processing Unit) 10, a memory 20, a storage 30, and an input / output unit 40. The CPU 10, the memory 20, the storage 30, and the input / output unit 40 are connected via a bus B so as to be able to communicate with each other.

[0015] The CPU 10 has an environmental data input unit 101, a transmission condition input unit 102, an observation area determination unit 103, an observation value evaluation unit 104, an observation value correction unit 105, and an observation data extraction position determination unit 106, and controls the operations of these respective components. Note that a GPU (Graphics Processing Unit) may be used instead of the CPU 10, or the CPU 10 and the GPU (Graphics Processing Unit) may be used in combination.

[0016] The environmental data input unit 101 inputs the ocean analysis data 301 (environmental information data) and the map data 302 from the storage 30 in accordance with an instruction input via the input / output unit 40. Further, the environmental data input unit 101 can also input data specified by the latitude, longitude, depth, time range, physical quantity, etc. of the ocean analysis data 301 specified via the input / output unit 40. When the environmental data observation plan formulation support apparatus 1 is connected to a network, the environmental data input unit 101 can input, via the network, atmospheric meteorological analysis data, etc. in addition to the ocean analysis data 301. Note that various data input by the environmental data input unit 101 are temporarily stored in the memory 20.

[0017] The transmission condition input unit 102 inputs the transmission condition data 303 from the storage 30 in accordance with an instruction input via the input / output unit 40. The input transmission condition data 303 are temporarily stored in the memory 20.

[0018] The observation area determination unit 103 inputs the observation route data 304 in accordance with an instruction input via the input / output unit 40, and determines the observation candidate area of an observation device (not shown) based on the observation route data 304. Further, the observation area determination unit 103 creates observation area data 306, which is data representing the determined observation candidate area, and outputs it to the storage 30. The observation area determination unit 103 determines, for example, an area within a predetermined allowable radius from the observation route as the observation candidate area, as shown in FIG. 2 described later.

[0019] The observation value evaluation unit 104 evaluates the observation value of the observation data at each position in the observation candidate area using the ocean analysis data 301 (environmental information data) in the observation candidate area determined by the observation area determination unit 103. The observation value evaluation unit 104, for example, weights each position in the observation candidate area with a weight (hereinafter referred to as "observation weight") for evaluating the observation value, and evaluates the observation value of each position in the observation candidate area based on the observation weight. In the present embodiment, the observation weight of each position in the observation candidate area is included in the observation area data 306.

[0020] The observed value correction unit 105 corrects the observed value evaluated by the observed value evaluation unit 104 based on the observation weight included in the observation area data 306.

[0021] The observation data extraction position determination unit 106 determines the extraction position of the observation data so that the observed value of the transmitted observation data is the highest according to the transmission condition of the observation data of the observation device (transmission condition data 303 described later).

[0022] The memory 20 is composed of, for example, a ROM (Read Only Memory), stores the ocean observation plan formulation support program 201 in the environmental data observation plan formulation support device 1, and temporarily stores information (data) necessary for various processes in each component of the CPU 10. The ocean observation plan formulation support program 201 is, that is, the program code of software that realizes the functions of each component of the CPU 10.

[0023] The storage 30 is composed of, for example, an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flexible disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, or a non-volatile memory, etc. The storage 30 stores environmental information data (ocean analysis data 301), map data 302, transmission condition data 303, observation route data 304, observation data extraction position data 305, and observation area data 306.

[0024] Environmental information data is time-series data of physical quantities at each position in the three-dimensional space of the underwater environment including the ocean and rivers. In the following description, ocean analysis data will be described as an example of environmental information data. The ocean analysis data 301 is three-dimensional time-series data obtained using ocean simulation for the ocean state. The ocean simulation obtains the temporal changes of physical quantities such as sea surface height, water temperature, salinity, and flow velocity by numerical analysis in a space represented by three axes of latitude, longitude, and depth (see FIG. 2 described later). In the ocean analysis data 301, the values of each physical quantity at each position in the three-dimensional space are stored. Note that as the ocean analysis data 301, data created and published by ocean research institutions or the like can also be used.

[0025] The map data 302 is two-dimensional or three-dimensional data defined as terrain data including the terrain of the seabed according to latitude and longitude. Further, the map data 302 may include information such as the positions of cities and rivers as necessary.

[0026] In the present embodiment, the transmission conditions include at least one or more of the maximum number of times of transmitting observation data, transmission coordinates, the maximum amount of transmitted data, and the number of extracted points of observation data. The transmission condition data 303 is data that defines the transmission conditions. Note that the transmission condition data 303 can be specified via the input / output unit 40 and may include data of conditions other than the above-described transmission conditions. For example, the transmission condition data 303 may include an allowable error radius (such as a radius of 10 km) with respect to the surfacing position in the specified observation route. In the present embodiment, for example, when the maximum number of times of transmitting observation data and the maximum amount of transmitted data are specified as the transmission condition data 303, the data capacity each time of transmission is set to "the maximum amount of transmitted data / the maximum number of times of transmission". Further, for example, when the maximum amount of transmitted data and the number of extracted points of observation data are specified as the transmission condition data 303, the data capacity each time of transmission is set to "the maximum amount of transmitted data / the number of extracted points".

[0027] Observation route data 304 is a set of data representing positions in a three-dimensional space for defining an observation route. The observation device continuously acquires observation data along the observation route (see R34 in FIG. 2 described later). Note that the data representing positions in the three-dimensional space is three-dimensional coordinate data or grid data (e.g., grid ID). In some cases, time data when passing through each position of the observation route is associated with the observation route data 304.

[0028] Observation data extraction position data 305 is data for defining at which positions to extract the observation data from all the observation data acquired by the observation device along the observation route, that is, coordinate data or grid data indicating the observation positions of the extracted observation data. Note that in some cases, observation time data of the observation data is associated with the observation data extraction position data.

[0029] Observation area data 306 is the surrounding area of the observation route generated by the observation area determination unit 103, and is a set of three-dimensional coordinate data or grid data representing an area (see R39 in FIG. 2 described later) that can be a candidate for observation by the observation device. In the present embodiment, an observation weight for evaluating the observation value of the observation data is defined for each position in the observation candidate area in the observation area data 306. The observation weight is a numerical value from "0" to "1", and is defined such that if it is "1", it is most easily observed, and if it is "0", it is not observed. That is, a position where the observation weight is "0" is a position outside the observation candidate area.

[0030] Note that various data stored in the storage 30 may be manually input via the input / output unit 40, or may be automatically created separately using an algorithm or the like.

[0031] The input / output unit 40 includes a keyboard 401, a mouse 402, and a display 403. The keyboard 401 and the mouse 402 are input devices, and the instruction information and the like input via the keyboard 401 and the mouse 402 are supplied to the CPU 10. The display 403 is a display device composed of a display device such as an LCD (Liquid Crystal Display) or an organic EL (Electro-luminescence) display. Note that the keyboard 401, the mouse 402, and the display 403 may be integrally formed as a touch panel, for example.

[0032] Next, the observation candidate area and the observation route in the environmental data observation plan creation support device 1 will be described. FIG. 2 is a diagram showing an image of the observation candidate area and the observation route in the environmental data observation plan creation support device 1 according to the present embodiment. The spatial area R31 shown in FIG. 2 is where the ocean analysis data 301 is represented in a three-dimensional spatial area. The upper surface R32 indicates the surface of the seawater, and the bottom surface R33 indicates the seabed. The starting point R35 and the ending point R36 respectively indicate the starting point and the ending point of the observation route on the upper surface R32. The passing point R37 indicates the passing point of the observation route on the bottom surface R33. The route R34 indicates the observation route from the starting point R35, passing through the passing point R37, and ending at the ending point R36.

[0033] Note that since the observation weight is set to be larger as the observation data along the route R34 is closer to the route R34, it is highly likely to be extracted as the observation data transmitted to a receiver such as a satellite. On the other hand, when it is away from the route R34 by a predetermined range, the observation weight becomes 0 and it falls outside the observation candidate area. In FIG. 2, the area R39 is an area within the range of the allowable radius R38 (predetermined allowable radius) from the route R34, and is an area where an observation device can be a candidate for observing environmental data along the route R34, that is, an observation candidate area. The area R39 (observation candidate area) changes according to the change of the allowable radius R38. For example, when the allowable radius R38 is "0", the observation candidate area becomes a set of coordinates or grids at the positions where the observation route (route R34) passes.

[0034] [Procedure for formulating environmental data observation plan] Next, the environmental data observation plan formulation process in the environmental data observation plan support device 1 will be described. FIG. 3 is a flowchart showing the procedure of the environmental data observation plan formulation process in the environmental data observation plan support device 1 according to the present embodiment. The processes described below start when the CPU 10 of the environmental data observation plan support device 1 receives an instruction input via the input / output unit 40.

[0035] First, the environmental data input unit 101 inputs ocean analysis data 301 from the storage 30 (step S10). In this process, the environmental data input unit 101 acquires the ocean analysis data 301 based on the latitude, longitude, depth, time range, physical quantity, etc. specified via the input / output unit 40. In this process, the environmental data input unit 101 may input map data 302, atmospheric meteorological analysis data, etc. in addition to the ocean analysis data 301.

[0036] Next, the transmission condition input unit 102 inputs transmission condition data 303 from the storage 30 (step S20).

[0037] Next, the observation area determination unit 103 inputs observation route data 304 from the storage 30 and determines an observation candidate area (step S30). In this process, the observation area determination unit 103 determines, for example, as shown in FIG. 2, an area R39 within a range of an allowable radius R38 from an observation route (route R34) as an observation candidate area based on the observation route data 304.

[0038] Next, the observation value evaluation unit 104 evaluates the observation value of the observation data at each position in the observation candidate area using the ocean analysis data 301 (step S40). In this process, the observation value evaluation unit 104 applies singular value decomposition (SVD) to the ocean analysis data 301 in the observation candidate area and evaluates the observation value using a low-dimensional model created by mode decomposition. Specifically, the ocean analysis data 301 in the observation candidate area can be expressed as in Equation (1).

[0039]

Number

[0040] In the above formula (1), X is the ocean analysis data 301 in the observation candidate area, Xntime,ndepth,nlat,nlon is the physical quantity at each coordinate position in the observation candidate area. ntime, ndepth, nlat, and nlon correspond to latitude, longitude, depth, and time, respectively. As shown in formula (1), the ocean analysis data 301 at each time in the row direction is arranged one-dimensionally and vectorized into a state vector. When there is only one type of physical quantity (for example, temperature), the length of the state vector is ndepth × nlat × nlon. When there are multiple physical quantities to be modeled in low dimensions, the state vector is extended in the row direction according to the arrangement method of formula (1). In the column direction, the ocean analysis data 301 vectorized into a state vector for each time is arranged. Here, the final data matrix X is n rows and m(ntime) columns.

[0041] As shown in formula (2), X is decomposed into the spatial POD mode U, the singular value matrix Σ, and the temporal POD mode V by applying singular value decomposition (SVD). T

[0042]

Number

[0043]

Number

[0044] Here, the importance for each observation point coordinate when approximating the physical quantity distribution by the low-dimensional model is taken as the observation value. On this premise, the low-dimensional spatial POD mode U shown in formula (4) 1:r ​Let it be the sensor candidate matrix W, and the pivot position obtained by performing QR decomposition is determined as the extraction position of the observation data (the position with high observation values). In the present invention, as described above, since observation weights are assigned to each position in the observation candidate region, the observation value evaluation unit 104 uses the low-dimensional space POD mode U shown in Equation (4). 1:r to only obtain it.

[0045]

Equation

[0046] Also, when obtaining the spatial POD mode by Equation (2), the number of modes is the number of data in the time direction of the data matrix X, that is, m. When constructing the low-dimensional model by Equation (3), it is truncated at r modes, but depending on the computer environment, it may not be truncated and the processing can also be performed using m spatial POD modes. Also, as data representing the observation value, data having values defined on the same spatial grid as the ocean analysis data 301 can be used. Also, for example, in a recent observation plan, it is possible to set a large observation weight in an area where no observation has been made and use it as the observation value.

[0047] Here, returning to the process of step S50 shown in FIG. 3, in the process of step S50, the observation value correction unit 105 corrects the observation value evaluated by the observation value evaluation unit 104 based on the observation weights included in the observation region data 306 determined by the observation region determination unit 103. Specifically, the observation value correction unit 105 performs calculations as in Equation (5) to calculate a new sensor candidate matrix W’, that is, the corrected value of the observation value.

[0048]

Equation

[0049] In the above formula (5), diag(OW) is a matrix in which the components of the vector OW obtained by one-dimensionally converting the observation region data 306 with the observation weights calculated in the observation region determination unit 103 as elements are diagonal components. The low-dimensional space POD mode U 1:r The product of and diag(OW) is calculated as a new sensor candidate matrix W'.

[0050] Note that the correction of the observed value is not limited to applying formula (5), and any method may be applied. Also, even when the data representing the observed value is data defined on the same spatial grid as the ocean analysis data 301, the observed value can be corrected by the same method as the above-described observed value correction method.

[0051] Next, the observation data extraction position determination unit 106 performs determination processing of the observation data extraction position so that the observed value (corrected observed value) of the observation data to be transmitted is the highest according to the transmission condition of the observation data (step S60). The determination processing of the observation data extraction position will be described in detail with reference to FIG. 4 described later. Also, when a position away from the input observation route is selected as the observation data extraction point, the observation route is corrected so as to include the extraction point position. At that time, for example, the observation route can be corrected so that the distance between the extraction point positions is minimized.

[0052] The environmental data observation plan formulation support device 1 formulates an environmental data observation plan including an observation route, an observation data extraction position, and transmission condition data 303. The environmental data observation plan formulated by the environmental data observation plan formulation support device 1 is registered in the observation device before observation. The observation device proceeds along the observation route, for example, reaches the observation data extraction position to perform observation, and floats at that position to transmit the observation data. Also, for example, when the transmission coordinates are specified in the transmission condition data 303, the observation device may float at the position of the transmission coordinates and extract and transmit the observation data at the observation data extraction position from the observed observation data.

[0053] [Determination Processing of Observation Data Extraction Position] Next, the determination process of the environmental data extraction position in the environmental data observation plan creation support device 1 will be described. FIG. 4 is a diagram showing the procedure of the determination process of the environmental data extraction position in the environmental data observation plan creation support device 1 according to the present embodiment. The process described below is called as a subroutine and executed in step S60 shown in FIG. 3.

[0054] First, the observation data extraction position determination unit 106 initializes a poslist, which is a list of positions (coordinates or grids) to be extracted, and an extraction position number k to 1 (step S601). In this process, the observation data extraction position determination unit 106 acquires, for example, the number of extraction points of the observation data included in the transmission condition data 303, and determines the length of the poslist based on the number of extraction points. For example, when the number of extraction points is 10, the length of the poslist is determined to be 10.

[0055] Next, the observation data extraction position determination unit 106 initializes a normlist, which is a list for storing the squared value of the norm of W' indicating the observation value (step S602). Note that the length of the normlist matches the number of elements n of the ocean analysis data 301.

[0056] Next, the observation data extraction position determination unit 106 initializes a counter i to 1 (step S603).

[0057] Next, the observation data extraction position determination unit 106 calculates the squared value of the norm of the i-th row vector of the sensor candidate matrix W' calculated by the observation value correction unit 105 and stores it in the normlist (step S604). Here, the vector of the i-th row of the sensor candidate matrix W' can be represented by W'[i, :].

[0058] Next, the observation data extraction position determination unit 106 increments the counter i (i + 1) (step S605).

[0059] Next, the observation data extraction position determination unit 106 determines whether the counter i is less than or equal to the number of elements n of the ocean analysis data 301 (step S606).

[0060] In the process of step S606, when the observation data extraction position determination unit 106 determines that the counter i is less than or equal to n (when step S606 is a Yes determination), it returns to the process of step S604 and repeatedly executes the processes of steps S604 to S606.

[0061] On the other hand, in the process of step S606, when the observation data extraction position determination unit 106 determines that the counter i exceeds n (when step S606 is a No determination), it sets the element position of the maximum value in normlist as idx (step S607).

[0062] Next, the observation data extraction position determination unit 106 stores the value of idx in poslist[k] (step S608).

[0063] Next, the observation data extraction position determination unit 106 updates the sensor candidate matrix W' according to formula (6) (step S609).

[0064]

Equation

[0065] In the above formula (6), W'[idx,:] is the row vector of the idx-th row of the sensor candidate matrix W', and it is the row vector with the maximum square of the norm.

[0066] Next, the observation data extraction position determination unit 106 increments the extraction position number k (k + 1) (step S610).

[0067] Next, the observation data extraction position determination unit 106 determines whether the extraction position number k is less than or equal to the number of extraction points (step S611).

[0068] In the process of step S611, when the observation data extraction position determination unit 106 determines that the extraction position number k is less than or equal to the number of extraction points (when step S611 is a Yes determination), it returns to the process of step S602 and repeatedly executes the processes of steps S602 to S611.

[0069] On the other hand, in the process of step S611, when the observation data extraction position determination unit 106 determines that the extraction position number k exceeds the number of extraction points (when step S611 is a No determination), the determination process of the observation data extraction position ends.

[0070] By the above-described determination process of the observation data extraction position, it is possible to identify a position with a high observation value along the observation route and determine an observation point position for limiting and transmitting only important observation data.

[0071] FIG. 5 is a diagram showing an observation data extraction position in the environmental data observation plan creation support apparatus 1 according to the present embodiment. FIG. 5A is a diagram showing an example of an observation data extraction position determined when the allowable radius R38 is set to 0. When the allowable radius R38 is "0", the observation candidate region is a set of positions through which the route R34 passes. Therefore, as shown in FIG. 5A, the determined observation data extraction positions (10 white points) are selected from the route R34.

[0072] FIG. 5B is a diagram showing an example of an observation data extraction position determined when the allowable radius R38 is set to a certain value and the observation weight is set to "1" at each position in the region R39. In the example shown in FIG. 5B, since the observation weights at each position are the same, the observation data extraction position determination unit 106 determines the observation data extraction position inside the region R39 based on the sensor candidate matrix W calculated using the above-described formula (4). The determined observation data extraction positions are indicated by the 10 white points shown in FIG. 5B.

[0073] FIG. 5C is a diagram showing an example of an observation data extraction position determined when the allowable radius R38 is set to a certain value and the observation weights corresponding to the respective positions in the region R39 are set to decrease as they are farther from the route R34. In the example shown in FIG. 5C, the observation data extraction position determination unit 106 determines the observation data extraction position inside the region R39 based on the sensor candidate matrix W' calculated using the above-described equation (6). In this case, since positions farther from the route R34 are less likely to be selected as the extraction position, as shown in FIG. 5C, the determined observation data extraction positions (for example, the white points P503, etc.) are distributed around the route R34.

[0074] In the examples of the observation data extraction positions shown in FIGS. 5B and 5C, the observation data extraction positions deviate somewhat from the route R34. In this case, the shortest path distance from the start point R35, passing through the observation data extraction position, to the end point R36 can be obtained by solving the shortest Hamiltonian path problem, and the route R34 can be updated. The updated route R34 may be appended to or updated in the observation route data 304 in the storage 30.

[0075] [Effect] As described above, the environmental data observation plan creation support device 1 according to the present embodiment evaluates the observation value corresponding to each position in the observation candidate region based on the transmission conditions such as the upper limit number of times of transmitting observation data, the upper limit amount of transmitted data, and the number of extraction points of the observation data. Further, the environmental data observation plan creation support device 1 determines a position with a high observation value as the observation data extraction position while satisfying the transmission conditions of the observation data. Therefore, according to the environmental data observation plan creation support device 1 according to the present embodiment, it is possible to plan an observation route with a high observation value while satisfying the transmission conditions such as the upper limit number of times of transmitting observation data and the upper limit amount of transmitted data.

[0076] In addition, the environmental data observation plan formulation support device 1 corrects the observed value by any means, and determines the position with a high observed value as the observation data extraction position based on the corrected observed value. Therefore, the environmental data observation plan formulation support device 1 facilitates the extraction of the position with a high observed value. Further, since the environmental data observation plan formulation support device 1 can obtain the shortest path distance from the observation data extraction position to the end point of the observation and update the observation route, it can satisfy the transmission conditions and improve the accuracy of the observation data.

[0077] <Second Embodiment> Next, the environmental data observation plan formulation support device 2 according to the second embodiment of the present invention will be described. The environmental data observation plan formulation support device 2 according to the present embodiment can support the formulation of an environmental data observation plan when the observation route is not completely determined and only the start point, the end point, and several passing points are determined. FIG. 6 is a block diagram showing a configuration example of the environmental data observation plan formulation support device 2 according to the present embodiment. As can be seen by comparing FIG. 6 with FIG. 1, the CPU 10a of the environmental data observation plan formulation support device 2 includes, in addition to each component of the CPU 10 shown in FIG. 1, a passing point input unit 107, a passing point tour circuit determination unit 108, and an observation route determination unit 109. Further, the environmental data observation plan formulation support device 2 includes an observation route candidate area specifying unit 110, an observation route candidate graph generation unit 111, and an observation route optimization unit 112. Here, the description of the same components of the environmental data observation plan formulation support device 2 and the environmental data observation plan formulation support device 1 shown in FIG. 1 is omitted.

[0078] In the present embodiment, the observation route data 304 is a three-dimensional coordinate or grid representing the positions of the start point, the end point, and the passing points of the observation route, and a plurality of passing points may exist. The passing point input unit 107 inputs the observation route data including the start point, the end point, and the passing points of the observation and temporarily stores it in the memory 20.

[0079] Based on the positions of the start point, end point, and passing points of the input observations, the passing point circuit determination unit 108 determines a circuit that passes through the passing points. Here, when there are multiple passing points, there are multiple circuits. Specifically, this will be described with reference to FIG. 7. FIG. 7 is a diagram showing an example of a circuit that passes through multiple passing points in the environmental data observation plan support apparatus 2 according to the present embodiment. In FIG. 7, the start point R71, end point R72, passing point R73, and passing point R74 of the observation route of the observation device in the spatial region R31 are shown. In this case, there is a first route (the route indicated by the solid arrow) that circulates in the order of the start point R71, passing point R73, passing point R74, and end point R72. Also, there is a second route (the route indicated by the dashed arrow) that circulates in the order of the start point R71, passing point R74, passing point R73, and end point R72. Therefore, the passing point circuit determination unit 108 determines the first route and the second route as circuits that pass through the passing points.

[0080] The observation route determination unit 109 selects and determines an observation route from the determined circuits according to a predetermined rule. Here, the predetermined rule includes, for example, a rule for selecting a circuit with the shortest distance, a rule for selecting a circuit with the shortest time, a rule for selecting a circuit with the minimum energy consumption, and the like. When the predetermined rule is a rule for selecting a circuit with the shortest distance, for example, the shortest circuit can be obtained from multiple circuits by a method for solving the shortest Hamiltonian path problem or the like. When the predetermined rule is a rule for selecting a circuit with the shortest time or the minimum energy consumption, for example, by utilizing the flow velocity data of the ocean analysis data 301, a circuit with the shortest time or the minimum energy consumption can be obtained from the fluid resistance acting on the observation device. Note that when there is only one passing point, there is only one circuit, so the observation route determination unit 109 determines the circuit as the observation route. In the example shown in FIG. 7, the observation route determination unit 109 determines the first route as the observation route.

[0081] The observation route candidate area specifying unit 110 specifies an observation route candidate area that is a candidate for passage as an observation route. Specifically, it will be described with reference to FIG. 8. FIG. 8 is a diagram showing an image of the observation route candidate area in the environmental data observation plan creation support apparatus 2 according to the present embodiment. Since the space area R31, the start point R71, the end point R72, the passing points R73 and R74 of the observation route shown in FIG. 8 are the same as these shown in FIG. 7, duplicate explanations are omitted. Further, FIG. 8 shows the observation route (the first route) determined by the observation route determination unit 109 described in FIG. 7. The observation route candidate area specifying unit 110 specifies, for example, an area R93 (the area surrounded by the dashed line) within a range of radius R91 along a reference route (for example, route R92) passing through each point of the observation route as the observation route candidate area. Also, by copying the space area R31, setting the value of each grid within the observation route candidate area to "1", and initializing the value of each grid outside the observation route candidate area to "0", the observation route candidate area can be represented on the space area R31. Note that the radius R91 for specifying the observation route candidate area may be set to, for example, a predetermined allowable radius, or may be set to any radius smaller than the predetermined allowable radius.

[0082] In the present embodiment, the observation value correction unit 105 performs the same processing as the processing of the observation value correction unit 105 described in FIG. 1, but uses the area R93 (observation route candidate area) shown in FIG. 8 instead of the area R39 (observation candidate area) shown in FIG. 2 as the processing target area. Then, an observation weight of "0 to 1" is assigned to each grid within the area R93, and the observation weight of each grid outside the area R93 is set to 0. When using the low-dimensional space POD mode U shown in Equation (4) as the observation value, the sensor candidate matrix W' can be created by determining whether each grid of the space area R31 is inside or outside the area R93. 1:r

[0083] ​The observation route candidate graph generation unit 111 generates an observation route candidate graph for optimizing the observation route in the observation route candidate area. Here, with reference to FIGS. 9 to 11, the generation of the observation route candidate graph will be described. FIG. 9 is a diagram showing a two-dimensional grid representation of the observation route candidate area in the environmental data observation plan creation support device 2 according to the present embodiment. In FIG. 9, the two-dimensional grid representation of the observation route candidate area (area R93) described in FIG. 8 is displayed as white grids, and the two-dimensional grid representation of the area outside the observation route candidate area is displayed as hatched grids.

[0084] The observation route candidate graph generation unit 111 sets each grid in the observation route candidate area (area R93) shown in FIG. 9 as a node, and sets the directions in which it is possible to move from each node to the surroundings as shown in FIG. 10. FIG. 10 is a diagram showing the directions in which it is possible to move from the grid of interest in the environmental data observation plan creation support device 2 according to the present embodiment. The black dots shown in FIG. 10 indicate an image in which a certain grid within the observation route candidate area (area R93) is the grid of interest and the grid of interest is the node R101. As shown in the figure, as the directions in which the node R101 can move to the surroundings, there are eight directions to move to each of the eight grids adjacent to the grid of interest (the grid where the node R101 is located).

[0085] The observation route candidate graph generation unit 111 calculates the inner product of each vector from each grid in the observation route candidate area (area R93) to the surrounding grids that can be moved to with respect to the vector indicated by the straight line from the start point R71 to the end point R72 of the observation route (see the arrow in FIG. 9). Then, the observation route candidate graph generation unit 111 creates an observation route candidate graph structure with only the vectors for which the calculated inner product value is positive as valid edges. FIG. 11 is a diagram showing the observation route candidate graph in the environmental data observation plan creation support device 2 according to the present embodiment. The white dots shown in FIG. 11 are notes corresponding to each grid in the observation route candidate area (area R93), and the black dots are notes corresponding to the start point R71 and the end point R72, respectively. The arrows (edges) connecting the notes indicate the movable paths.

[0086] The observation route optimization unit 112 uses the observation value corrected by the observation value correction unit 105 and the observation route candidate graph generated by the observation route candidate graph generation unit 111 to identify the path with the highest observation value from the observation route candidate graph. Here, the moving cost of each edge is set to a value obtained by attaching a negative sign to the observation value of the destination grid, and an algorithm that can consider negative costs, such as the Bellman-Ford method, is applied to identify the path with the minimum moving cost from the starting point R71 to the ending point R72. The path with the minimum moving cost is, that is, the path with the maximum total observation value, and is output as the optimal observation route. When using the sensor candidate matrix W' as an index indicating the observation value, the sensor candidate matrix W' is updated according to Equation (7) each time the element of the destination is determined.

[0087] [Number]

[0088] In the above Equation (7), tgt is the position of the destination grid.

[0089] [Observation Route Determination Process] Next, the observation route determination process in the environmental data observation plan formulation support device 2 will be described. FIG. 12 is a flowchart showing the procedure of the observation route determination process in the environmental data observation plan formulation support device 2 according to the present embodiment. The processes described below start when the CPU 10a of the environmental data observation plan formulation support device 2 receives an instruction input via the input / output unit 40. Note that the processes in step S10 and step S40 shown in FIG. 12 are the same as the processes in step S10 and step S40 shown in FIG. 3, respectively, and thus redundant explanations are omitted.

[0090] After the process of step S40, the passing point input unit 107 inputs observation route data including the starting point, ending point, and passing points of the observation (step S71).

[0091] Next, the passing point circuit determination unit 108 determines a circuit passing through the passing points based on the positions of the start point, end point, and passing points of the input observation (step S72). In this process, the passing point circuit determination unit 108 determines the passing point circuit by the method described with reference to FIG. 7.

[0092] Next, the observation route determination unit 109 selects and determines an observation route from the plurality of passing point circuits determined by the passing point circuit determination unit 108 according to a predetermined rule (step S73). After the process of step S73, the observation route determination process ends.

[0093] [Observation Route Optimization Process] Next, the observation route optimization process in the environmental data observation plan creation support device 2 will be described. FIG. 13 is a flowchart showing the procedure of the observation route optimization process in the environmental data observation plan creation support device 2 according to the present embodiment. The processes described below are executed after the observation route determination process described with reference to FIG. 12.

[0094] First, the observation route candidate area specifying unit 110 specifies an observation route candidate area that is a passing candidate as an observation route (step S81). In this process, the observation route candidate area specifying unit 110 specifies the observation route candidate area by the method described with reference to FIG. 8.

[0095] Next, the observation value evaluation unit 104 evaluates the observation value of the marine analysis data 301 in the observation candidate area for each grid in the observation candidate area (step S40).

[0096] Next, the observation value correction unit 105 corrects the observation value data evaluated by the observation value evaluation unit 104 based on the observation weight in the observation route candidate area specified by the observation route candidate area specifying unit 110 (step S82).

[0097] Next, the observation route candidate graph generation unit 111 generates an observation route candidate graph (see FIG. 11) for optimizing the observation route (step S83).

[0098] Next, the observation route optimization unit 112 uses the observation value corrected by the observation value correction unit 105 and the observation route candidate graph generated by the observation route candidate graph generation unit 111 to identify the path with the highest observation value as the optimal observation route (step S84). After the process of step S84, the observation route optimization process ends.

[0099] Note that in the present embodiment, after determining the optimal observation route, the environmental data observation plan formulation support device 2 performs the determination process of the observation data extraction position described with reference to FIG. 4. Therefore, the environmental data observation plan formulation support device 2 according to the present embodiment can obtain the same effects as the environmental data observation plan formulation support device 1 according to the first embodiment.

[0100] [Effect] As described above, the environmental data observation plan formulation support device 2 according to the present embodiment determines an observation route passing through the passing points from the viewpoints of the shortest distance, the shortest time, or the minimum energy consumption, etc., using the start point, the end point, and several passing points of the observation. Further, the environmental data observation plan formulation support device 2 specifies an observation route candidate area for the determined observation route, and determines the path with the highest observation value from the observation route candidate graph in the observation route candidate area as the optimal observation route. Therefore, according to the environmental data observation plan formulation support device 2 according to the present embodiment, the same effects as the environmental data observation plan formulation support device 1 according to the first embodiment can be obtained, and when the observation route is not completely set, the optimal observation route can be identified.

[0101] Note that the present invention is not limited to the above-described embodiments, and various other application examples and modification examples can of course be taken without departing from the gist of the present invention described in the claims. For example, each of the above-described embodiments has described the configuration of the environmental data observation plan formulation support device in detail and specifically for the purpose of easily explaining the present invention, and is not necessarily limited to having all the configurations described. Also, it is possible to replace a part of the configuration of the embodiment described here with the configuration of another embodiment, and furthermore, it is also possible to add the configuration of another embodiment to the configuration of a certain embodiment. Also, it is possible to add, delete, or replace other configurations for a part of the configuration of the embodiment. Also, the control lines and information lines show those considered necessary for explanation, and not necessarily all the control lines and information lines on the product are shown. In fact, it may be considered that almost all the components are interconnected.

Description of Reference Numerals

[0102] 1, 2... Environmental data observation plan formulation support device, 10, 10a... CPU, 20... Memory, 30... Storage, 40... Input / output unit, 101... Environmental data input unit, 102... Transmission condition input unit, 103... Observation area determination unit, 104... Observation value evaluation unit, 105... Observation value correction unit, 106... Observation data extraction position determination unit, 107... Passing point input unit, 108... Passing point circuit determination unit, 109... Observation route determination unit, 110... Observation route candidate area specification unit, 111... Observation route candidate graph generation unit, 112... Observation route optimization unit, 201... Ocean observation plan formulation support program, 301... Ocean analysis data, 302... Map data, 303... Transmission condition data, 304... Observation route data, 305... Observation data extraction position data, 306... Observation area data, 401... Keyboard, 402... Mouse, 403... Display

Claims

1. An observation area determination unit that determines an observation candidate area of an observation device based on observation route data; An observation value evaluation unit that evaluates the observation value of the observation data at each position in the observation candidate area using the environmental information data in the observation candidate area; An observation value correction unit that corrects the observation value of each position in the observation candidate area; An observation data extraction position determination unit that determines the extraction position of the observation data according to the transmission condition of the observation data so that the observation value of the transmitted observation data is the highest. The environmental data observation plan formulation support device is provided with: An environmental data observation plan formulation support device.

2. The transmission condition includes at least one or more of the transmission upper limit number of times of the observation data, the transmission coordinates, the transmission data upper limit amount, and the extraction number of points of the observation data. The environmental data observation plan formulation support device according to Claim 1.

3. The environmental information data is time series data of physical quantities at each position in a three-dimensional space of an underwater environment including the ocean and rivers. The environmental data observation plan formulation support device according to Claim 2.

4. The observation route data is a set of data representing positions in the three-dimensional space for defining the observation route. The environmental data observation plan formulation support device according to Claim 3.

5. The data representing positions in the three-dimensional space is three-dimensional coordinate data or grid data. The environmental data observation plan formulation support device according to Claim 4.

6. The observation area determination unit determines, as the observation candidate area, an area within a range of a predetermined allowable radius from the observation route. The environmental data observation plan formulation support device according to Claim 5.

7. The observation value evaluation unit weights an observation weight for evaluating the observation value for each position in the observation candidate area, and evaluates the observation value of each position in the observation candidate area. The environmental data observation plan formulation support device according to Claim 6.

8. The observation value correction unit corrects the observation value evaluated by the observation value evaluation unit based on the observation weight. The environmental data observation plan formulation support device according to Claim 7.

9. The observation route data is a three-dimensional coordinate or grid representing the position of each of the start point, end point, and passing points of the observation route, and a plurality of passing points may exist. The environmental data observation plan formulation support device according to Claim 2.

10. A passing point circuit determination unit that determines a circuit passing through the passing point based on the positions of the start point, the end point, and the passing point of the observation route; An observation route determination unit that selects and determines an observation route from the determined circuit according to a predetermined rule; An observation route candidate region specifying unit that specifies an observation route candidate region that is a passing candidate as the observation route; An observation route candidate graph generation unit that generates an observation route candidate graph for optimizing the observation route in the observation route candidate region; An observation route optimization unit that uses the observation route candidate graph and the observation value to specify, as the observation route, the path with the highest observation value from the observation route candidate graph. The environmental data observation plan formulation support device according to claim 9.

11. A step of determining an observation candidate region based on observation route data; A step of evaluating the observation value of the observation data at each position in the observation candidate region by using the environmental information data in the observation candidate region; A step of correcting the observation value at each position in the observation candidate region; A step of determining the extraction position of the observation data so that the observation value of the transmitted observation data is the highest according to the transmission condition of the observation data. An environmental data observation plan formulation support method.

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