Search support device, search support method, and search support program

Abstract

This invention provides a search support device, a search support method, and a search support program that can assist in formulating an optimal search plan. [Solution] The operation support device includes a recommendation means that determines the search area assigned to the detection node and the movement route within that search area as a recommendation for the search, based on the detection performance and operating conditions of the detection node in the search area and the probability of the existence of the target to be searched, and an output means that outputs the recommendation determined by the recommendation means.

Description

[Technical Field]

[0001] The present disclosure relates to a search support device, a search support method, and a search support program. [Background Art]

[0002] Patent Document 1 describes a method for determining an optimal arrangement matching the current situation within a realistic calculation time for a transmitting / receiving device for an underwater object search support device that searches for underwater objects. Patent Document 1 also describes a method for determining sensor arrangement in a multistatic sonar system. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent No. 6220716 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] In the method described in Patent Document 1, arrangement optimization is performed by increasing or decreasing the number of transmission sensors and reception sensors so that a search area satisfies a fixed search coverage rate. However, in actual operation, increasing, decreasing, or moving sensors is not easy, so it is necessary to study a method with higher feasibility. In addition, the method described in Patent Document 1 aims to search the entire search area uniformly without omission. Therefore, when the target position is predicted or an area where no target exists is known, this method may not provide an optimal sensor arrangement.

[0005] The present disclosure has been made in view of these problems. One object of the present disclosure is to provide a search support device, a search support method, and a search support program that can support the formulation of an optimal search plan. [Means for Solving the Problem]

[0006] The search support device based on this disclosure includes a recommendation means for determining the search area of ​​the detection node and the movement path within that search area as a recommendation for the search, based on the detection performance and operating conditions of the detection node in the search area and the probability of the presence of the target to be searched. Includes an output means for outputting recommendations.

[0007] The search support method based on this disclosure involves a computer determining the search area and movement path within that area as a search recommendation, based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, and outputting the recommendation.

[0008] The search support program based on this disclosure causes a computer to perform a recommendation process that determines the search area assigned to each detection node and the movement path within that area as a recommendation for the search, based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target to be searched, and an output process that outputs the recommendation. [Effects of the Invention]

[0009] This disclosure can help in developing an optimal search plan. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram illustrating the functional configuration of a search support device. [Figure 2] This is a flowchart illustrating the operation of a search support device. [Figure 3] This is an explanatory diagram showing an example of setting simulation conditions and target information. [Figure 4] This is a diagram illustrating a sensor performance map. [Figure 5] This figure shows an example of visualizing the initial target probability distribution map. [Figure 6]This is a diagram illustrating search responsibility areas when a search target area is searched by four sonar nodes. [Figure 7] This is a diagram illustrating movement paths of sonar nodes within shared search areas. [Figure 8] This is a flowchart illustrating the operation of a simulation unit in step S211. [Figure 9] This is a diagram illustrating a probability distribution of targets that may intrude into a search target area. [Figure 10] This is a diagram illustrating an avoidance maneuver of a target. [Figure 11] This is a diagram illustrating a result obtained by subtracting a target existence probability according to a detection probability. [Figure 12] This is a diagram illustrating a target search evaluation result output to a display device. [Figure 13] This is a flowchart showing a modified example of the operation of a search support device. [Figure 14] This is a block diagram illustrating the hardware configuration of a computer. [Figure 15] This is a block diagram illustrating main parts of a search support device.

Mode for Carrying Out the Invention

[0011] Various techniques for searching for underwater objects are known. For example, Document 2 (Japanese Unexamined Patent Application Publication No. 2023-080637) describes that sonars used for searching for underwater objects are broadly classified into two types: passive sonars and active sonars.

[0012] A passive sonar is a device that captures sound waves emitted by a target present in water or on the water surface, and calculates the position and azimuth of the target. On the other hand, an active sonar radiates sound waves into water from a transmitter, detects reflected sound from the target object with a receiver, and measures the position, distance, and speed of the target object based on the time from when the radiated sound is emitted until the reflected sound is detected and the detection azimuth of the reflected sound.

[0013] Monostatic operation refers to a mode in which reception by a passive sonar is performed by a single sensor, or a mode in which a single sensor performs both transmission and reception in an active sonar. In contrast, multistatic operation refers to a mode in which the transmitter and receiver of an active sonar are disposed at separated positions. In particular, a multistatic mode in which two sensors are mounted on one vehicle, one sensor transmits a wave, and the other sensor receives the wave to measure the position, distance and speed of a target is called bistatic operation.

[0014] The appropriate differentiation between passive sonar and active sonar, the selection of an operation method among monostatic, multistatic and bistatic, and the setting of transmission parameters for active sonar all vary depending on the acoustic wave propagation conditions and search objectives. Note that transmission parameters include, for example, transmission frequency, transmission pulse length, transmitted sound pressure level, and transmission depression angle.

[0015] When actually searching for a target using a sonar, it is necessary to consider not only the selection of the sonar type and operation method, but also unique characteristics of a sonar node (a vehicle equipped with a sonar or a fixed-position sonar itself) such as movement speed and action restrictions. Furthermore, it is also necessary to consider which sonar nodes are to be used for the search.

[0016] A sonar operator is required to determine the type, arrangement and operation method of sonar nodes to be used based on the environmental conditions of the sea area and the behavior of the search target.

[0017] In recent years, due to the diversification of sonar nodes and operation methods, the options for search methods have increased, and the number of factors that a sonar operator must consider has also increased. It is difficult to quantitatively evaluate the method for maximizing the search efficiency of a sonar, and the current situation is that most current search methods are determined depending on the know-how of veteran sonar operators.

[0018] Reference 3 (Japanese Patent Publication No. 2020-193885) describes a method for performing simulations that test multiple behavioral patterns of underwater objects when implementing monostatic or bistatic operation using multiple sensors. Reference 3 also describes generating multiple simulation results for a planned sensor arrangement and evaluating the effectiveness of a specific sensor arrangement plan through statistical analysis.

[0019] However, reference 3 does not mention combinations of different types of sensors. Furthermore, the sensor placement evaluation method described in reference 3 mainly assumes fixed-position sensors. Therefore, this sensor placement evaluation method cannot be applied when sensors move autonomously over time, for example, when sensors are mounted on a predetermined vehicle and move around the search area.

[0020] Document 4 (Japanese Patent Publication No. 6984739) describes a method for calculating the movement path of a sensor, taking into account the sensor's effective search range which changes depending on location and environmental information. However, Document 4 does not mention cases where multiple sensors with different movement limitations cooperate to conduct a search, nor does it recommend methods for operating the sensors.

[0021] Document 5 (Japanese Patent Publication No. 2023-131817) describes an evaluation and support device that predicts the target's location and expected course based on information about the target's discovery point, and determines a sensor placement that allows for efficient searching. However, the technology described in Document 5 requires clear input of target behavior information into the evaluation and support device, resulting in a search that relies on the operator's assumptions.

[0022] This disclosure was made in view of these issues. The search support device of this disclosure calculates the allocation and placement (movement path) of search areas that are suited to the characteristics of sonar nodes as search recommendations, and further evaluates the effectiveness of the target search and outputs the results. In addition, the device performs simulations to calculate the search effectiveness when the search is carried out according to the recommendations, and supports judgment on feasibility and the possibility of achieving the objective. Furthermore, the device takes into account the time-changing surrounding environment and recommends changes to the search areas, placement (movement path), and sonar node types of sonar nodes. With these features, the search support device of this disclosure outputs search recommendations and the search effectiveness thereof, and supports the formulation of an optimal search plan.

[0023] Embodiments of this disclosure will be described below with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and redundant explanations are omitted as necessary for clarity. Unless otherwise specified, predetermined values ​​such as set values ​​and thresholds are stored in advance in a storage device accessible from the device that uses those values. Unless otherwise specified, the storage unit is composed of one or any number of storage devices.

[0024] Embodiment 1. [Explanation of the structure] The search support device of this embodiment will now be described. Figure 1 is a block diagram showing an example of the configuration of the search support device.

[0025] A detection node used in the search for underwater targets is a sensor unit equipped with sensors that has functions such as search, detection, and positioning. Detection nodes can take the form of fixed types, which are fixed to the seabed, underwater structures, buoys, etc., and mobile types, which are mounted on vehicles or ships and can perform detection while moving. In this embodiment, a sonar node equipped with sonar will be used as an example of a detection node. However, the sensors used in the detection node are not limited to sonar; radar, cameras, other sensing devices, etc. may also be used.

[0026] When formulating a search plan for an underwater target, the search support device 100 inputs and selects necessary parameters from an operating terminal, such as the purpose of the search, information from sensors to be used in the search, and the expected path of the target to be searched (hereinafter also simply referred to as the target). Based on this information, the search support device 100 recommends the search area and movement path of the sonar node. Furthermore, the search support device 100 simulates how the target would move if the search were conducted based on the recommended results, and calculates and outputs the expected value for finding the target within the search time. In this embodiment, the simulation unit 107 of the search support device 100 assumes that the target will reach its destination while avoiding the search by the sonar node. The target is assumed to take action to avoid the sonar node's search when it detects it.

[0027] Furthermore, the search support device 100 outputs the time-dependent changes in the position and movement of sonar nodes and targets used in the search to a display device such as a display unit in a manner that is easy for the operator to recognize. This supports the operator in formulating a search plan.

[0028] As shown in Figure 1, the search support device 100 includes an input unit 101, a control unit 102, a storage unit 103, a condition setting unit 104, a simulation unit 105, a sonar operation recommendation unit 106, a simulation unit 107, and an output unit 108.

[0029] The input unit 101 accepts input operations from users such as operators and other personnel and inputs the information.

[0030] The control unit 102 has the function of inputting and outputting information to the storage unit 103 based on the information input by the input unit 101. The control unit 102 also has the function of controlling the condition setting unit 104, the simulation unit 105, the sonar operation recommendation unit 106, the simulation unit 107, and the output unit 108 based on the information input by the input unit 101.

[0031] The memory unit 103 stores information about all sonar nodes available for search. This information includes, for example, the type of sensor installed on each sonar node, the available sensor specifications, speed range (maximum and minimum speed), movement restrictions, the time required to deploy the sensors, and the corresponding sensor operation method for each sensor.

[0032] Furthermore, the memory unit 103 stores the processing results of the condition setting unit 104, the simulation unit 105, the sonar operation recommendation unit 106, and the simulation unit 107.

[0033] The condition setting unit 104 has the function of setting the simulation conditions necessary for conducting the simulation based on the input information. Here, the input information includes not only the information input by the input unit 101, but also the information output from the storage unit 103 based on the information input by the input unit 101.

[0034] The simulation unit 105 has the function of calculating the performance of sonar nodes used for the search based on the simulation conditions set by the condition setting unit 104. The simulation unit 105 also has the function of calculating an initial target existence probability distribution, which shows the distribution of the probability of the existence of a target in the search area, through simulation. For example, the simulation unit 105 calculates the performance of sonar nodes at each point in the search area and the time course of the probability of the existence of the target.

[0035] In this embodiment, the distribution of the probability of a target's existence in the search area is called the target existence probability distribution. In particular, the initial target existence probability distribution before considering the effect of sonar node searching on the target is called the initial target existence probability distribution.

[0036] The sonar operation recommendation unit 106 has the function of calculating the search area and movement route within the search time for each sonar node as a recommendation for the search, based on the setting results of the condition setting unit 104 and the calculation results of the simulation unit 105.

[0037] For example, the sonar operation recommendation unit 106 determines the search area of ​​the sonar node as a recommendation, based on the detection performance and operating conditions of the sonar node in the search area and the probability of the target's presence. The sonar operation recommendation unit 106 also determines the movement path of the sonar node within the search area as a recommendation, based on the detection performance and operating conditions of the sonar node in the search area and the probability of the target's presence. The operating conditions of the sonar node include, for example, at least one of the sonar node's speed range and operating restrictions.

[0038] The simulation unit 107 has the function of conducting simulations that simulate the target's behavior. The simulation unit 107 also has the function of predicting how the target will move when a search is conducted based on the calculation results (i.e., recommendations) of the sonar operation recommendation unit 106, and the function of evaluating the search effectiveness of the search based on the prediction results. As part of the evaluation of the search effectiveness, the simulation unit 107 evaluates, for example, the likelihood of detecting the target by a search based on the recommendations over time.

[0039] The output unit 108 has the function of outputting some or all of the processing results of the condition setting unit 104, the simulation unit 105, the sonar operation recommendation unit 106, and the simulation unit 107. For example, the output unit 108 can output and store the processing results in the search support device 100 or the storage unit (not shown) of an external device. The output unit 108 can also output and display the processing results on a display device (not shown). The processing results include, for example, recommendations such as the search area and movement route of the sonar node, prediction results that predict how the target of the search will move if the search is carried out according to the recommendations, and evaluation results that evaluate the search effectiveness if the search is carried out according to the recommendations. Therefore, the operator can recognize this information by checking the output results.

[0040] [Explanation of operation] Next, the operation of the search support device will be explained. Figure 2 is a flowchart illustrating the operation of the search support device 100. Figure 2 shows an example of the recommendation and evaluation process for sonar operation by the search support device 100.

[0041] The condition setting unit 104 sets the simulation conditions necessary for conducting the simulation based on the information input by the input unit 101 (step S201). The condition setting unit 104 sets the simulation conditions, for example, the location and size of the search area, the search time, and the purpose of the search. In this embodiment, the purpose of the search is to prevent the target from passing through the search area.

[0042] Next, the condition setting unit 104 sets information regarding the sonar nodes to be used for the search (step S202). The condition setting unit 104 sets the type of sensor mounted on each sonar node and the specifications of the usable sensors as information regarding the sonar nodes. The condition setting unit 104 also sets the operating conditions for each sonar node (for example, the speed range and operating restrictions of the sonar node) as information regarding the sonar nodes. The condition setting unit 104 can also set information regarding sonar nodes and sensors to be used preferentially. This information is stored in advance in the storage unit 103.

[0043] Next, the condition setting unit 104 sets information related to the target to be searched (hereinafter also referred to as target information) (step S203). As target information, the condition setting unit 104 sets, for example, the type and purpose of the target to be searched, the target specifications necessary for hydrometric prediction calculations, the speed range, the expected target route (hereinafter also referred to as the expected target route), and pre-appearance information before the start of the search (i.e., the time and location in which the target was previously discovered). This information is stored in advance in the storage unit 103. Furthermore, the purpose of the target in this embodiment is to reach the destination point without being detected by the sonar node.

[0044] Water acoustics forecasting is a technique that predicts sound wave propagation and determines detection probability by considering factors such as water temperature and salinity. Details of water acoustics forecasting are disclosed, for example, in reference 6 (Urick, Robert J. "Underwater Acoustics," Kyoto Tsushinsha, January 23, 2013, p. 247).

[0045] Here, the setting of simulation conditions and target information will be explained with reference to Figure 3. Figure 3 is an explanatory diagram showing an example of setting simulation conditions and target information.

[0046] Figure 3 shows the search area 301, which is set as a simulation condition. Figure 3 also shows the target's starting point 302 and destination point 303, which are set as target information. The starting point 302 is set in correspondence with the departure time. It is unknown which path the target will take to reach the destination point 30. Therefore, a predicted target path 304 is set as the target's predicted target path. Multiple predicted target paths can be set, in which case a probability of the target passing through each predicted target path is associated with it. Predicted target paths are set, for example, as straight lines connecting points. Furthermore, the width of possible paths the target may take (for example, corresponding to the dotted lines shown in Figure 3) can be individually set for each predicted target path.

[0047] The condition setting unit 104 sets environmental information for the area to be searched (step S204). The condition setting unit 104 sets parameters commonly used in hydrometric prediction calculations, such as water temperature, wind speed, seabed topography, and seabed reflection loss, as environmental information. Measured values, statistical values, and predicted values ​​of such environmental information are stored in advance in the storage unit 103.

[0048] The search support device 100 may perform each setting process in steps S201 to S204 based on input information from the input unit 101 according to the operator's input, or it may perform it based on information previously stored in the storage unit 103. Furthermore, the search support device 100 may perform each setting process in steps S201 to S204 in the order shown in Figure 2, or it may perform them simultaneously or in a different order.

[0049] Next, the simulation unit 105 performs water-side prediction calculations for each sonar node and sensor specification set in step S202. The simulation unit 105 calculates the sensor performance of each sensor for each point within the search target area, such as each point in a grid-like division of the search target area (step S205). This provides a sensor performance map showing the expected sensor performance when a specific sonar node (sensor) is placed at a specific location.

[0050] The sensor performance map will now be explained. Figure 4 is an example of a sensor performance map. Figure 4 shows a search target area 401 divided into a grid. Figure 4 also shows the water measurement prediction results for a specific sonar node (sensor). Specifically, the water measurement prediction result at point A is shown as water measurement prediction result 402, and the water measurement prediction result at point B is shown as water measurement prediction result 403. Water measurement prediction result 402 and water measurement prediction result 403 represent the detection probability of the sonar node at the corresponding point. In the example shown in Figure 4, the coverage area of ​​water measurement prediction result 402 is wider than that of water measurement prediction result 403. Thus, even with the same sensor and specifications, sensor performance differs depending on the location. Also, since sensor performance changes when the speed of the sonar node changes, the simulation unit 105 calculates a sensor performance map for each speed that the sonar node can take.

[0051] Next, the simulation unit 105 sets representative search parameters for each sensor to be used from step S208 onward (step S206). Representative search parameters for a sensor are the optimal or standard sensor parameters used when the sensor performs a search. For example, the simulation unit 105 can select one arbitrary sensor and its parameters from the conditions set in step S202 for each sonar node. Alternatively, the simulation unit 105 can use the results of the water measurement prediction calculation performed in step S205 to compare all combinations of sonar nodes and sensor parameters and select the one with the best performance.

[0052] Next, the simulation unit 105 calculates the probability of the target being present at each point within the search area based on the target information set in step S203 (step S207).

[0053] In this embodiment, the distribution of the probability of a target's presence at each location in the search area, quantified on a map, is called the target presence probability distribution map. In particular, the initial target presence probability distribution of the initial state, before considering the effect of sonar node searching on the target, is quantified on a map and is called the initial target presence probability distribution map.

[0054] Figure 5 shows an example of a visualization of the initial target existence probability distribution map. In Figure 5, the probability of the target's existence is represented by the intensity of the color, with darker colors indicating a higher probability of the target's existence and a greater likelihood of the target being passed.

[0055] For example, the simulation unit 105 calculates the probability of a target being present at each point within a search area divided into a grid, and creates an initial target probability distribution map. In this case, the grid coarseness in the initial target probability distribution map does not have to be the same as that of the sensor performance map.

[0056] Next, the sonar operation recommendation unit 106 calculates the search area for each sonar node to be used for the search (step S208).

[0057] The sonar operation recommendation unit 106 determines the search area for each sonar node based on the sensor performance map calculated in step S205, the initial target existence probability distribution map calculated in step S207, and the sonar node's operating conditions (at least one of speed range and operation restrictions) set in step S202. By considering the speed range and operation restrictions of the sonar nodes, the sonar operation recommendation unit 106 can output a search area that reflects the actual size and shape of the search range that the sonar nodes (and onboard sensors) can achieve. Sonar nodes can navigate a wider area within a predetermined period by increasing their speed, but this comes at the cost of reduced sensor performance, which is a trade-off.

[0058] Figure 6 illustrates the search areas when searching a target area with four sonar nodes. Figure 6 shows the target area 601 being equally divided into four search areas. When a sonar node is deployed in each search area to conduct a search, the sensor performance changes depending on the type and speed of the sonar nodes placed in each area, as shown by circle 602 in Figure 6, resulting in different target detection rates (detectability) relative to the initial target probability distribution. In step S208, in order to maximize the search efficiency of the entire target area, the method of dividing each search area (e.g., determining its position and area), the allocation of sonar nodes to each search area, and the speed of the sonar nodes are determined.

[0059] Determining the search area, allocating sonar nodes, and setting the sonar node speeds involve optimizing a vast number of combinations. The sonar operation recommendation unit 106 performs brute-force calculations for all options and can select the search area division method, sonar node allocation, and speed that have the highest expected value for finding the target. The sonar operation recommendation unit 106 can also derive the optimal solution through mathematical optimization calculations or quantum annealing calculations using quantum computing technology. Furthermore, the sonar operation recommendation unit 106 can also use approximate solution calculation algorithms such as simulated annealing and genetic algorithms.

[0060] In the flowchart shown in Figure 2, process 209, which includes steps S210 and S211, is a process that takes into account the passage of time by dividing the search time into n steps of unit time t × n, and repeating parameter updates and calculations for each step.

[0061] In step S210, the sonar operation recommendation unit 106 calculates the position of the sonar node that maximizes the target search efficiency in each step (each unit of time) for each search area calculated in step S208 (step S210). This calculates the movement path of the sonar node throughout the entire search time. Here, the position of the sonar node in each step is determined and the movement path within the search time is optimized. In doing so, the sonar operation recommendation unit 106 takes into account the sensor performance map calculated in step S205, the initial target presence probability distribution map calculated in step S207, and the sonar node operation conditions set in step S202 (e.g., speed range and movement restrictions).

[0062] Figure 7 illustrates the movement paths of sonar nodes within a search area. Figure 7(A) shows the movement path of a sonar node with no movement restrictions. On the other hand, Figure 7(B) shows the movement path of a sonar node with movement restrictions that minimize course changes.

[0063] As shown in Figure 7, the sonar node is subject to the behavioral restrictions set in step S202. In each step, the sonar operation recommendation unit 106 calculates an appropriate position to move to the next step, within a range where the probability of a target being present is high, the sonar node can reach it at its speed, and the behavioral restrictions are met.

[0064] The sonar operation recommendation unit 106 performs the processes in steps S208 and S210 to determine the search area and the movement route within the search area of ​​the sonar node as a search recommendation.

[0065] In step S211, the simulation unit 107 evaluates the effectiveness of the search if it were conducted according to the recommendations, based on the initial target probability distribution and the search recommendations (e.g., sonar node and sensor types, sensor specifications, search area assignments, movement paths, etc.) (step S211).

[0066] In step S211, the simulation unit 107 takes the search area and movement path (position at each step (unit time)) of each sonar node calculated in steps S208 and S210 as input and calculates the sensor performance of the sonar node at each step using hydrometric prediction calculation. Furthermore, the simulation unit 107 simulates the behavior of targets affected by the search by the sonar nodes to reproduce fluctuations in the target existence probability distribution and evaluate the search effect by the sonar nodes. In this embodiment, it is assumed that the target existence probability distribution within the search area is calculated from the statistics of target behavior when a large number of target candidates each act using Monte Carlo simulation. However, other methods may be used, such as simulating the behavior of a single target.

[0067] Step S211 will be explained in detail with reference to Figure 8. Figure 8 is a flowchart illustrating the operation of the simulation unit in step S211.

[0068] In the flowchart shown in Figure 8, process 801, which includes steps S802 to S805, is a process that takes into account the passage of time by dividing the search time into n steps of unit time t × n and performing calculations at each step.

[0069] In step S802 of Figure 8, the simulation unit 107 calculates the probability distribution of targets that may enter the search area in the step being calculated.

[0070] Figure 9 illustrates the probability distribution of targets that may enter the search area. The simulation unit 107 can predict the position the target has reached up to the calculation step (for example, corresponding to the predicted position 901 shown in Figure 9) from the target's departure point and departure time set in step S203. Based on the predicted target position, the target's predicted path (for example, corresponding to the predicted target path 902 shown in Figure 9), the target's speed range, and the elapsed time, the simulation unit 107 can calculate the probability distribution of targets that may enter the search area (for example, corresponding to the target probability distribution 903 shown in Figure 9).

[0071] In step S803 of Figure 8, the simulation unit 107 simulates the target's behavior according to the target's behavior rules and updates the target's probability distribution as a result. The target's behavior rules include, for example, that the target basically moves to the destination point along the predicted target path, but if it detects the presence of a sonar node being searched, it takes evasive action to avoid detection.

[0072] Figure 10 illustrates target evasion maneuvers. Figure 10 shows an example where sonar node 21 is positioned in the direction of target 22's movement, and also shows the detection range of sonar node 21 and target 22. Note that the detection range of target 22 is wider than that of sonar node 21.

[0073] In the example shown in Figure 10, if target 22 continues moving in the same direction for a predetermined time, sonar node 21 will be located within the detection range of target 22. However, at this time, target 22 is not located within the detection range of sonar node 21. In other words, target 22 unilaterally detects the presence of sonar node 21. In response, target 22 takes evasive maneuvers to avoid being detected by sonar node 21. In Figure 10, this evasive maneuver is shown as evasive maneuver 23.

[0074] In this embodiment, the objective of the target is set in step S203 as "to reach the destination point without being detected by sonar nodes." However, in actual search situations, the movement of the target changes depending on the seabed topography, marine environment, and objective of the target. The simulation unit 107 may perform a more detailed simulation by adding further rule-based behavioral conditions according to these conditions, or it may create a target movement / avoidance model using reinforcement learning with training data.

[0075] In step S804 of Figure 8, the simulation unit 107 determines whether the target existence probability distribution is within the sensor detection range of each sonar node in the step being calculated. Through the processing in step S804, the simulation unit 107 calculates the target's detectability.

[0076] In step S804, the simulation unit 107 takes the position information of each sonar node calculated in step S210 as input and calculates the sensor performance of the sonar node in the step being calculated by hydrometric prediction calculation. This gives the detection range of each sonar node. The simulation unit 107 considers the target presence probability distribution within the obtained detection range as "detected" and subtracts the corresponding target presence probability according to the detection probability. Alternatively, the simulation unit 107 may set a threshold for the detection probability, and if it exceeds the threshold, set the target presence probability at that location to 0 and treat it as completely detected.

[0077] Figure 11 illustrates the result of subtracting the target existence probability according to the detection probability. In Figure 11, the sonar node (sensor) 1101 and its detection range 1102 are displayed on the initial target existence probability distribution map. In the example shown in Figure 11, the intensity of the color within the detection range 1102 is lighter, indicating that the target existence probability is decreasing (i.e., detection is possible). Detection probability can be expressed not only as a binary value such as 0 or 1, but also as the expected value of detection calculated from the target existence probability and the detection probability.

[0078] In step S805 of Figure 8, the simulation unit 107 calculates the probability distribution of targets that reflect the detection probability in the step being calculated (hereinafter also referred to as the detection target probability distribution) and the probability distribution of targets that have moved away from the search area (hereinafter also referred to as the departing target probability distribution).

[0079] After the calculations for the unit time t × n steps up to step S805 are completed, the simulation unit 107 performs an overall evaluation of the entire search time (step S806). Here, the simulation unit 107 sums the probability distribution of the detected target and the probability distribution of the escaping target for all n steps, and outputs the result as the target search evaluation result in step S211.

[0080] In step S212 of Figure 2, the output unit 108 outputs the target search evaluation results calculated up to step S211. This allows the search support device 100 to provide the operator with recommendations for searching using sonar nodes and their evaluation results.

[0081] The output unit 108 outputs the target search evaluation results to a display device, such as a display device. Figure 12 is an example of the target search evaluation results output to the display device. Figure 12(A) shows the search area 1201, the position (sensor position) of each sonar node 1202, and the target presence probability distribution 1203 at step n within the search time. The output unit 108 can further provide search recommendations using sonar nodes and their evaluation results visually by showing the movement and changes of the sonar nodes and the target presence probability distribution in a time series for each step using a video or the like.

[0082] Figure 12(B) shows the sum of the target departure probability distributions for targets that have moved and left the search area by the end of the search. Specifically, Figure 12(B) shows the predicted target path 304 of the target in the initial state (i.e., a state where the effect of sonar node search on the target is not considered). Also, Figure 12(B) shows the probability distribution of targets that have left the search area due to the effect of sonar node search as a histogram 305. The search support device 100 can record the position (for example, a grid-like divided area) that the target passed through when it left the search area, and represent the target departure probability distribution as a histogram, making it clear from which position the target departed.

[0083] Furthermore, the output format of the output unit 108 is not limited to screen display. For example, the output unit 108 may output the target search evaluation results in video format, or it may output the probability distribution in CSV file format or the like. The operator can also utilize the data output in such formats for post-event analysis.

[0084] Generally, target search using multiple sonar nodes involves a combination of numerous factors, including the selection of sensor specifications, the setting of search areas, and the allocation of sonar nodes. These factors create a vast number of combinatorial problems in determining the optimal operational method for sonar nodes to move and search for targets within the search time. Traditionally, the operational method of sonar nodes has relied on the operator's expertise.

[0085] The search support device 100 of this embodiment recommends a method for operating sonar nodes based on the sensor performance (i.e., detection performance) and the predicted target path (i.e., predicted target path) at each point within the search area. Furthermore, the search support device 100 performs simulations on the recommended results and quantitatively evaluates their effectiveness. With this configuration, the search support device 100 can provide a rational basis for sonar node operation and support the operator's decision-making.

[0086] Furthermore, the search support device 100 can output the movement of sonar nodes and fluctuations in the target probability distribution in a time-series video format. This allows operators to easily identify areas for operational improvement during the search. In addition, the search support device 100 can compare and visualize the search effectiveness from start to finish for each operational method used for the sonar nodes and sensors in the search. This allows operators to visually understand at what time and location a particular operational method should or should not be adopted, contributing to the formulation of operational plans. As a result, it becomes possible to formulate search plans based on the setting of search areas and the placement of sonar nodes (sensor placement) to maximize search efficiency using multiple sonar nodes.

[0087] [Differentiation] This embodiment is not limited to the examples described above. This embodiment allows for a variety of modifications that can be understood by those skilled in the art. For example, this embodiment can also be implemented in the form shown in the following modified examples.

[0088] In the example described above, one search area was assigned to one sonar node in step S208. However, it is possible to perform searches using multiple nodes, for example, by having two sonar nodes search one search area, or by having all available sonar nodes search the entire target area. In this case, it is conceivable to specify multiple sonar nodes to search within the same search area in step S202 and impose restrictions on their actions. For example, imposing a constraint that certain sonar nodes must act within a certain distance from each other can simulate the communication range, while conversely, imposing a constraint that requires a distance greater than a certain distance can simulate collision avoidance.

[0089] As another variation, the search support device 100 can also be configured to have a function to recommend the addition of sonar nodes. In step S211, the search support device 100 evaluates the search effectiveness for the target for each unit time within the search time and calculates a target presence probability distribution that reflects the detection probability for each unit time. At this time, if the search is not carried out sufficiently due to insufficient sonar nodes, sensor performance, movement speed, etc., the target presence probability may increase in a part of the search area.

[0090] In such cases, adding a sonar node can be considered as a countermeasure. Figure 13 is a flowchart showing a modified operation of the search support device. As shown in Figure 13, after step S211, the search support device 100 determines whether the probability of a target being present exceeds a threshold within a certain time (step S1301). If the probability of a target being present exceeds a threshold within a certain time (step S1301: YES), the search support device 100 adds a sonar node and performs recalculation from step S202. At this time, the target information setting in step S204 inherits the probability of a target being present used in the previous step S1301. The sonar node to be added here may be automatically selected by assigning an evaluation of ease of deployment to a sonar node pre-registered in the memory unit 103, or it may be manually selected by the operator. With this configuration, the sonar operation recommendation unit 106 can add a sonar node and re-determine the recommendation if the search effect does not meet predetermined evaluation criteria (i.e., if the probability of a target being present exceeds a threshold within a certain time).

[0091] As another variation, the search support device 100 can be configured to take over the target probability distribution at the end of the search and the final position of the sonar node after obtaining the target search result evaluation in step S211, and repeat the recalculation from step S202. In this case, the sonar operation recommendation unit 106 can reallocate the search area based on the target probability distribution that has changed due to the search. The sonar operation recommendation unit 106 may also exclude areas where the target probability is below a predetermined threshold from the search area, thereby reducing the size of the search area. Based on the search area excluding the areas not to be searched, the sonar operation recommendation unit 106 can determine the search area assigned to each sonar node.

[0092] Furthermore, the search support device 100 can be configured to handle various search situations by changing the objective and actions of the target set in step S203. For example, if the target is set not to move, it can simulate the search for a stationary target, and if the objective of the target is to prevent intrusion into a specific area, it can simulate a search using sonar nodes to prevent intrusion.

[0093] As another variation, the search support device 100 can be configured to reset environmental information in step S204 and, accordingly, recalculate sensor performance in step S205. In this case, the search support device 100 will re-execute the processes from step S204 onward based on the updated environmental information. Furthermore, when the search support device 100 performs recalculations using the simulation results of the search situation up to that point, it uses the result of the target existence probability distribution obtained in step S211 before the recalculation as the initial target existence probability distribution calculated in step S207. In addition, the search support device 100 can perform recalculations by inheriting the final position of the sonar node before the recalculation as the initial position of the sonar node set in step S201.

[0094] Furthermore, if there is no need to change the search area, the search support device 100 can omit unnecessary processing, such as retaining the output result of step S208 as it was before recalculation.

[0095] The embodiment described above is an example of a search using only sonar nodes. However, the sensors are not limited to sonar, and radar, cameras, and other sensing devices can be used in combination. For example, in step S202, the search support device 100 sets the characteristics of the relevant sensor or sensor node equipped with the sensor, and in step S205, it calculates the sensor performance. This allows the search support device 100 to simulate and evaluate searches using various types of sensors.

[0096] [Explanation of effects] Next, the effects of this embodiment will be described. In this embodiment, the simulation unit 105 simulates the performance of each sonar node used for the search at each point within the search area. The simulation unit 105 also performs a time-course simulation of the area where the target is located, based on environmental information and the purpose of the target, and outputs the probability of the target being located in the initial state (i.e., a state in which the effect of sonar node searching on the target is not considered).

[0097] The sonar operation recommendation unit 106 takes the detection performance and target presence probability of the sonar nodes calculated by the simulation unit 105 as input and outputs the search area and position (movement path) of each sonar node, taking into account the passage of time, as a search recommendation. At this time, the sonar operation recommendation unit 106 can determine the search area and position (movement path) taking into account the passage of time based on the operating conditions of each sonar node (e.g., speed range and movement restrictions). The sonar operation recommendation unit 106 can output information indicating the search area and the position of the sonar node simultaneously, or output it individually according to the operator's selection instructions. At this time, the sonar operation recommendation unit 106 can output recommendation results that are more realistic by reflecting the individual movement restrictions and behavioral characteristics of each sonar node.

[0098] The simulation unit 107 uses the output results of the simulation unit 105 and the sonar operation recommendation unit 106 to simulate and predict how the target will move if the search is conducted according to the recommendations. The simulation unit 107 conducts the simulation assuming that the target has a predetermined objective and acts according to set behavioral rules. Then, the simulation unit 107 simulates the search effect on the target based on the prediction results and calculates the result as the target search evaluation result. The evaluation of the search effect by the simulation unit 107 can reflect changes in search conditions due to changes or additions of sonar nodes.

[0099] These functional components enable the search support device 100 to output recommendations for the search area and movement path of sonar nodes, taking into account past target location information and assumed movement paths, as well as sensor performance, thereby supporting the formulation of search plans. Furthermore, the search support device 100 can easily test the impact on target search when changing the operation method of the sonar nodes based on the recommended results, or when using other sonar nodes, thus effectively supporting the operator in formulating search action plans.

[0100] Each function (each process) in the above embodiment can be implemented by a computer having a processor, memory, etc. For example, a program for implementing the method (process) in the above embodiment may be stored in a storage device (storage medium), and each function may be implemented by executing the program stored in the storage device with a processor.

[0101] Figure 14 is a block diagram illustrating the hardware configuration of computer 1000. Computer 1000 is any computer. For example, computer 1000 is a stationary computer such as a personal computer or a server machine. Alternatively, computer 1000 is a portable computer such as a smartphone or a tablet device. Computer 1000 may be a dedicated computer designed to implement the search support device 100, or it may be a general-purpose computer.

[0102] Computer 1000 has a processor 1001, a storage device 1002, memory 1003, a bus 1004, an input / output interface 1005, and a network interface 1006.

[0103] Processor 1001 is a variety of processing units, including CPUs (Central Processing Units), GPUs (Graphics Processing Units), FPGAs (Field-Programmable Gate Arrays), and DSPs (Digital Signal Processors).

[0104] The storage device 1002 is, for example, a non-transitory computer-readable medium. Non-transitory computer-readable media include various types of tangible storage media. Specific examples of non-transitory computer-readable media include semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM).

[0105] Memory 1003 is a main memory system implemented using RAM (Random Access Memory) or similar technologies. Memory 1003 temporarily stores data when the processor 1001 executes processing.

[0106] Bus 1004 is a data transmission path for the processor 1001, memory 1003, storage device 1002, input / output interface 1005, and network interface 1006 to send and receive data to and from each other. However, the method of connecting the processor 1001 and the others to each other is not limited to bus connection.

[0107] The input / output interface 1005 is an interface for connecting the computer 1000 with input / output devices. For example, input devices such as keyboards and output devices such as display devices are connected to the input / output interface 1005.

[0108] The network interface 1006 is an interface for connecting computer 1000 to a network. This network may be a LAN (Local Area Network) or a WAN (Wide Area Network).

[0109] The storage device 1002 stores a program that implements each of the functional components in the above-described embodiments and examples. The processor 1001 reads this program into the memory 1003 and executes it to implement each of the functional components in the above-described embodiments and examples.

[0110] The search support device 100 may be implemented by one computer 1000 or by multiple computers 1000. In the latter case, the configuration of each computer 1000 does not need to be the same and can be different.

[0111] Each functional component in the above embodiments and examples may be implemented by a combination of the hardware and software described above, or by hardware (for example, a hardwired electronic circuit).

[0112] Next, an overview of this disclosure will be described. Figure 15 is a block diagram illustrating the overview of a search support device. The search support device 10 according to this disclosure (for example, corresponding to a search support device 100) includes a recommendation means 11 (implemented by a sonar operation recommendation unit 106 in an embodiment) that determines the search area assigned to the detection node and the movement path within the search area as a recommendation for the search, based on the detection performance (for example, corresponding to sensor performance) and operating conditions (for example, corresponding to speed range and movement restrictions) of the detection node in the search area and the probability of the existence of the target to be searched (for example, corresponding to the probability distribution of the existence of the target), and an output means 12 (implemented by an output unit 108 in an embodiment) that outputs the recommendation. With such a configuration, it is possible to support the formulation of an optimal search plan.

[0113] The search support device 10 can be configured to include a simulation means (implemented by a simulation unit 107 in this embodiment) that predicts how the target of the search will move if the search is carried out according to the recommendations. The output means 12 can also output the prediction results from the simulation means.

[0114] The simulation means can evaluate the effectiveness of a search based on prediction results that predict how the target of the search will move if the search is conducted according to the recommendations. In addition, the output means 12 can output the evaluation results from the simulation means (for example, equivalent to the target search evaluation results).

[0115] The simulation method calculates the likelihood of detecting the target (for example, information indicating the expected value of detection, which is derived from the probability of the target existing and the probability of detection) as an evaluation of the search effectiveness.

[0116] If the search effectiveness does not meet the predetermined evaluation criteria, the recommended method 11 can add detection nodes to be used in the search and re-determine the recommendation.

[0117] Recommended method 11 excludes areas within the search area where the probability of the target being found is below a predetermined threshold, and determines the search area assigned to each detection node based on the remaining search area.

[0118] The search support device 10 can be configured to include a simulation means (implemented by a simulation unit 105 in this embodiment) that calculates the detection performance of detection nodes at each point within the search area and the time course of the probability of the existence of the target object. The recommendation means 11 then determines a recommendation based on the calculation results from the simulation means.

[0119] The technology disclosed herein is applicable not only to the sonar field but also to various other fields such as radar, passive radio wave sensors, active optical wave sensors (such as LiDAR), and optical cameras.

[0120] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Each embodiment can be combined with other embodiments as appropriate.

[0121] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate.

[0122] Some or all of the above embodiments may also be described as follows, but are not limited to the following:

[0123] (Note 1) Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, a recommendation means for determining the search area assigned to the detection nodes and the movement route within that search area is provided as a recommendation for the search. The system includes an output means for outputting the aforementioned recommendations. A search support device characterized by the following features.

[0124] (Note 2) The system includes a simulation means for predicting how the target of the search will move if the search is conducted in accordance with the aforementioned recommendations. The output means is capable of outputting the prediction result. Search support device as described in Appendix 1.

[0125] (Note 3) The simulation means evaluates the effectiveness of the search based on the prediction results, which predict how the target of the search will move if the search is conducted in accordance with the recommendations. The output means is capable of outputting the evaluation result. Search support device as described in Appendix 2.

[0126] (Note 4) The simulation means calculates the likelihood of detecting the target as an evaluation of the search effectiveness. Search support device as described in Appendix 3.

[0127] (Note 5) If the search effectiveness does not meet the predetermined evaluation criteria, the recommended means adds detection nodes to be used in the search and re-determines the recommendation. Search support device as described in Appendix 3 or Appendix 4.

[0128] (Note 6) The recommended method excludes areas within the search area where the probability of finding the target is below a predetermined threshold, and determines the search area assigned to each detection node based on the search area excluding these excluded areas. A search support device as described in any of the appendices 1 through 5.

[0129] (Note 7) The system includes a simulation method for calculating the detection performance of detection nodes at each point within the search area and the time course of the probability of the presence of the target object. The recommendation means determines the recommendation based on the calculation results from the simulation means. A search support device as described in any of the appendices 1 through 6.

[0130] (Note 8) The operating conditions of a detection node include at least one of the speed range and operating restrictions of the detection node. A search support device as described in any of the appendices 1 through 7.

[0131] (Note 9) Computers Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, the search area assigned to each detection node and the movement path within that area are determined as a search recommendation. Output the aforementioned recommendation. A search support method characterized by the following features.

[0132] (Note 10) On the computer, Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, a recommendation process is performed to determine the search area assigned to the detection nodes and the movement path within that search area as a recommendation for the search. The output process that outputs the aforementioned recommendations A search support program to facilitate the execution of the search.

[0133] Furthermore, some or all of the configurations described in Appendices 2 to 8, which are dependent on Appendice 1 above, may also be dependent on Appendices 9 and 10 in the same way as those described in Appendices 2 to 8. Moreover, not limited to Appendices 1, 9, and 10, some or all of the configurations described as appendices may also be dependent on various hardware, software, various recording means for recording software, or systems, without departing from the embodiments described above. [Explanation of Symbols]

[0134] 10,100 Search and Support Devices 11 Recommended methods 12 Output means 101 Input Section 102 Control Unit 103 Storage section 104 Condition Setting Section 105 Simulation Department 106 Sonar Operation Recommendations 107 Simulation Department 108 Output section 1000 computers 1001 Processor 1002 Storage device 1003 memory 1004 Bus 1005 Input / Output Interface 1006 Network Interface

Claims

1. Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, a recommendation means for determining the search area assigned to the detection nodes and the movement route within that search area is provided as a recommendation for the search. The system includes an output means for outputting the aforementioned recommendations. A search support device characterized by the following features.

2. The system includes a simulation means for predicting how the target of the search will move if the search is conducted in accordance with the aforementioned recommendations. The output means is capable of outputting the prediction result. The search support device according to claim 1.

3. The simulation means evaluates the effectiveness of the search based on the prediction results, which predict how the target of the search will move if the search is conducted in accordance with the recommendations. The output means is capable of outputting the evaluation result. The search support device according to claim 2.

4. The simulation means calculates the likelihood of detecting the target as an evaluation of the search effectiveness. The search support device according to claim 3.

5. If the search effectiveness does not meet the predetermined evaluation criteria, the recommended means adds detection nodes to be used in the search and re-determines the recommendation. The search support device according to claim 3.

6. The recommended method excludes areas within the search area where the probability of finding the target is below a predetermined threshold, and determines the search area assigned to each detection node based on the search area excluding these excluded areas. A search support device according to any one of claims 1 to 5.

7. The system includes a simulation method for calculating the detection performance of detection nodes at each point within the search area and the time course of the probability of the presence of the target object. The recommendation means determines the recommendation based on the calculation results from the simulation means. A search support device according to any one of claims 1 to 5.

8. The operating conditions of a detection node include at least one of the speed range and operating restrictions of the detection node. A search support device according to any one of claims 1 to 5.

9. Computers Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, the search area assigned to each detection node and the movement path within that area are determined as a search recommendation. Output the aforementioned recommendation. A search support method characterized by the following features.

10. On the computer, Based on the detection performance and operating conditions of the detection nodes in the search area and the probability of the presence of the target object, a recommendation process is performed to determine the search area assigned to the detection nodes and the movement path within that search area as a recommendation for the search. The output process that outputs the aforementioned recommendations A search support program to facilitate the execution of the search.

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