JP2015190896A - Target detection supporting system and method of the same - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a target detection supporting system capable of accurately finding a target existing underwater.SOLUTION: The target detection supporting system is a system for supporting the detection of a target existing underwater. The system includes: a processing unit for acquiring detection information of an object detected by each of a plurality of kinds of sensors; a generation unit for generating information of target candidates on the basis of the detection information; an analysis unit for analyzing the information of the target candidates using a predetermined filter; an output unit for outputting a result of the analysis; and a reception unit for receiving a selection from the target candidates.

Description

  The present invention relates to a target detection support system and method for supporting detection of a target in water.

  Conventionally, for example, a sensor integrated system disclosed in Patent Document 1 is known as a system for detecting the position of a target based on detection information from a plurality of types of sensors. In this sensor integrated system, the movement trajectory of a target is estimated and output by combining observation data observed by a plurality of sensors such as a radar and a camera. Known techniques such as MHT, JPDA, filtering using the size and speed of the target, and PF are used to estimate the movement trajectory.

JP 2012-163495 A

  Since electromagnetic waves and the like are not easily transmitted underwater, acoustic sensors that detect sound waves propagating in water are mainly used for underwater target detection. However, the propagation of sound waves is affected by underwater conditions such as changes in water temperature, seabed topography, and noise. In addition, marine organisms and water masses having characteristics such as the same size and moving speed as the target are present in the water. Due to such special circumstances in water, it is very difficult to detect a target in water compared to detection of a target in the air, on the water, and on the ground. For this reason, it is not easy to estimate the trajectory of the target in water, and it is very difficult to discover the presence / absence of the target itself.

  The sensor integrated system is intended to automatically estimate the movement trajectory of the target. For this reason, it is difficult to find a target while considering the condition in the water with complicated conditions, and it is difficult to efficiently find the target in the water.

  The present invention has been made to solve such a problem, and an object of the present invention is to provide a target detection support system and method for finding a target in water more accurately.

  A target detection support system according to an aspect of the present invention is a system that supports detection of a target in water, and a processing unit that acquires detection information of a target detected by each of a plurality of types of sensors; A generation unit that generates target candidate information based on the detection information, an analysis unit that analyzes the target candidate information using a predetermined filter, an output unit that outputs a result of the analysis, and the target candidate A reception unit that receives a selection from the inside.

  In the target detection support system, the accepting unit may accept resetting of the filter condition before accepting selection from the target candidates.

  The target detection support system may further include a control unit that creates a parameter for controlling the sensor based on the selected target candidate information.

  The target detection support system further includes a storage unit that stores the detection information, and after receiving a selection from the target candidates, when the reception unit receives a regeneration condition of the target candidate information, the generation The unit may regenerate the target candidate information based on the detection information read from the storage unit according to the regeneration condition.

  In the target detection support system, the output unit may output characteristics regarding the target candidate information together with the position of the target candidate.

  In the target detection support system, the sensor includes an acoustic sensor including a transmitter and a plurality of receivers, and the processing unit acquires the detection information and observation error information from the acoustic sensor, and includes the detection information in the detection information. An extended detection region generating unit that generates an extended detection region in which an error distribution based on the observation error information is reflected at the position of the target object, and a vote adding unit that sets the number of votes corresponding to the extended detection region in a voting space And an area specifying unit that specifies an area with a large number of votes in the voting space as an area where the object exists.

  A target detection support method according to an aspect of the present invention is a target detection support method for supporting detection of a target in water, and acquires detection information of an object detected by each of a plurality of types of sensors, Target candidate information is generated based on the detection information, a result obtained by analyzing the target candidate information using a predetermined filter is output, and selection from the target candidates is accepted.

  The present invention has the above-described configuration, and has an effect of providing a target detection support system and method for finding a target in water with higher accuracy.

  The above object, other objects, features, and advantages of the present invention will become apparent from the following detailed description of the preferred embodiments with reference to the accompanying drawings.

It is a block diagram which shows the main structures of the target detection assistance system which concerns on Embodiment 1 of this invention. It is a flowchart which shows an example of the target detection support method of the target detection support system of FIG. It is the chart showing the information on the target object acquired by various sensors, and the information on the target candidate based on the information on this target object. It is a flowchart which shows an example of the target detection assistance method of the target detection assistance system which concerns on Embodiment 2 of this invention. It is a block diagram which shows the main structures of the target detection assistance system which concerns on Embodiment 3 of this invention. It is a flowchart which shows an example of the target detection support method of the target detection support system of FIG. It is a block diagram which shows a part of structure of the target detection assistance system which concerns on Embodiment 4 of this invention. It is a figure for demonstrating an extended detection area | region. It is a figure which shows the position of the target object detected by two receivers, and its extended detection area. It is a figure which shows the number of votes set to the voting space and its voting box. It is a flowchart which shows an example of the target detection assistance method of the target detection assistance system of FIG. It is a block diagram which shows the structure of a part of target detection assistance system which concerns on Embodiment 5 of this invention. It is a flowchart which shows an example of the target detection support method of the target detection support system of FIG.

  Hereinafter, embodiments of the present invention will be specifically described with reference to the drawings. In the following description, the same or corresponding elements are denoted by the same reference symbols throughout all the drawings, and redundant description thereof is omitted.

(Embodiment 1)
FIG. 1 is a block diagram showing a main configuration of a target detection support system 100 according to the first embodiment. As shown in FIG. 1, the target detection support system 100 is a system that is located in the air, on land, on water, or in water, and supports detecting a target in the water. The target detection support system 100 is connected to the sensor 200 and the terminal device 300. The target is an object selected as a target from among the objects detected by the sensor 200, and examples thereof include an underwater vehicle that moves in water and an underwater object that exists in water.

  The sensor 200 is located in the air, land, water, or water, and acquires (detects) information related to an object (object) that is in the air, water, or water. Objects also include objects that move in the air, on water, or in water. The sensor 200 adds sensor identification information and sensor position information to the detected object information (detection information), and outputs them to the target detection support system 100 as sensor information. However, when the position of the sensor 200 is specified in advance and the sensor position information is associated with the sensor identification information, the sensor position information may not be output.

  The sensor 200 includes, for example, an acoustic sensor 210, a radar sensor 220, a light wave sensor 230, a reverse detection device (ESM) 240, a magnetic detection device (MAD) 250, an automatic ship identification device (AIS) 260, a communication device 270, and an enemy ally identification. The apparatus (IFF) 280 is comprised. However, the sensor 200 is not particularly limited as long as it is a plurality of different types of sensors 200. For this reason, all of these need not be used as the sensor 200 of the target detection support system 100. The sensor 200 preferably includes a sensor that can detect a wide range of objects in water, for example, an acoustic sensor 210. Moreover, it is preferable to include a sensor that can detect an object on the water over a wide range, for example, a radar sensor 220.

  The acoustic sensor 210 is a sensor that detects sound waves. The active acoustic sensor 210 emits sound waves and receives sound waves reflected by the object, and the sound waves emitted from the object and the sound waves emitted by the active acoustic sensor. There is a passive acoustic sensor 210 that receives sound waves reflected by an object. The radar sensor 220 is a sensor that radiates radio waves and receives radio waves reflected by an object. The light wave sensor 230 is a sensor that detects a light wave, and is, for example, a camera. The reverse detection device 240 is a sensor that receives radio waves radiated from an object. The magnetic detection device 250 is a sensor that detects a change in a geomagnetic field generated by an object. The automatic vessel identification device 260 is a device that receives information about the vessel that is issued by the vessel. The communication device 270 is a device that receives information about an object from another communication device. The enemy ally identification device 280 is a device that inquires an object about an enemy ally and receives a response.

  The terminal device 300 is a device for operating the target detection support system 100, and for example, a computer having an input unit 310 and a display unit 320 is used. The input unit 310 is a device for inputting information (operation information) from an operator to the target detection support system 100. The display unit 320 is a display that displays information output from the target detection support system 100, for example. However, the display unit 320 may be a printer or the like as long as it can output information. The terminal device 300 is provided separately from the target detection support system 100, but may be included in the target detection support system 100.

  The target detection support system 100 is configured by a computer, for example, and includes a calculation unit 110 and a storage unit 120. For example, the arithmetic unit 110 is configured by a CPU, and the storage unit 120 is configured by an internal memory, an external storage device, or the like. The storage unit 120 stores a target detection support program and related information. The related information includes, for example, correspondence between sensor position information and sensor identification information, and marine information. The ocean information includes the type and position of an underwater object known in advance such as a shipwreck, the type and position of a seabed topography, and past water temperature measurement results. The calculation unit 110 includes an acquisition unit 130, a detection information processing unit (processing unit) 140, a target candidate information processing unit 150, and a reception unit 160.

  The acquisition unit 130 acquires sensor information from the sensor 200 and outputs the sensor information to the detection information processing unit 140 based on the sensor identification information. When acquiring the sensor information, the acquisition unit 130 may include the acquisition time as detection time information of the sensor 200 in the sensor information. This detection time information represents the time when the sensor 200 detects the object. However, when the sensor 200 detects the object, the time may be acquired, and this time may be included in the sensor information as detection time information and output to the target detection support system 100.

  The detection information processing unit 140 acquires and processes the detection information of the sensor information, and generates information on the object detected by each sensor 200. However, part or all of the object information may be generated by the sensor 210. In this case, the detection information processing unit 140 uses the detection information generated by the sensor 210 as information on the object.

  The detection information processing unit 140 includes, for example, an acoustic information processing unit 141, a radar information processing unit 142, a light wave information processing unit 143, a reverse detection information processing unit 144, a magnetic information processing unit 145, a ship identification information processing unit 146, and a communication information processing. Part 147 and an enemy ally information processing part 148. One detection information processing unit 140 is provided corresponding to one sensor 200. However, one detection information processing unit 140 may be provided for the plurality of sensors 200.

  Based on the sensor information from the acoustic sensor 210, the acoustic information processing unit 141 generates information on the object such as the position, course, and speed of the object on the water or in the water. Examples of sensor information from the acoustic sensor 210 include the position of the transmitter and receiver of the acoustic sensor 210, the direction of the received sound wave, the time from when the sound wave is transmitted until it is received, and the received sound wave. Examples include frequency and frequency shift.

  Based on the sensor information from the radar sensor 220, the radar information processing unit 142 generates information on the object such as the position, course, speed, and shape of the object in the air or on the water. The sensor information from the radar sensor 220 includes, for example, the position of the transmitter and receiver of the radar sensor 220, the direction of the received radio wave, the time from when the radio wave is transmitted until it is received, Time is given.

  Based on the sensor information from the light wave sensor 230, the light wave information processing unit 143 generates information on the object such as the shape, course, and speed of the object in the air, underwater, or on the water. The sensor information from the light wave sensor 230 includes, for example, the position of the light wave sensor 230, a visible image or infrared image capturing the light wave, the direction of the received light wave, and the time of the received light wave.

  Based on the sensor information from the reverse detection device 240, the reverse detection information processing unit 144 generates information on the target such as the type and direction of the target that is a radio wave radiation source. Examples of the sensor information from the reverse detection device 240 include the position of the reverse detection device 240 and the direction and frequency of the received radio wave.

  The magnetic information processing unit 145 generates information on the object such as the constituent material of the object based on the sensor information from the magnetic detection device 250. Examples of the sensor information from the magnetic detection device 250 include the position of the magnetic detection device 250 and a change in the received magnetic field.

The ship identification information processing unit 146 is based on the sensor information from the automatic ship identification device 260.
Information on the object such as ship identification information, position, course, and speed is generated. Examples of the sensor information from the automatic ship identification device 260 include ship identification information, position, course, and speed.

  Based on information from the communication device 270, the communication information processing unit 147 generates information on the object such as identification information, position, course, and speed of the object. Examples of sensor information from the communication device 270 include ship identification information, position, course, and speed.

  The enemy ally information processing unit 148 generates information on the object such as the enemy ally discrimination of the object based on the sensor information from the enemy ally identification device 280. Examples of the information from the enemy ally identifying device 280 include a response to a question issued by the enemy ally identifying device 280.

  The target candidate information processing unit 150 includes a generation unit 151, an analysis unit 152, and an output unit 153. The generation unit 151 generates information on at least one target candidate based on the information on the target object. The analysis unit 152 sets a filter condition for analyzing the target candidate information, and analyzes the target candidate information using a predetermined filter. The filter condition represents the feature amount of the target, and includes, for example, the assumed position, speed, and size of the target. The filter condition may be a predetermined value or may be a value input by the operator from the input unit 310 via the receiving unit 160. The analysis method is not particularly limited. For example, an existing feature amount analysis technique such as multivariate analysis can be used. The output unit 153 outputs the analysis result to the display unit 320.

  The accepting unit 160 accepts operation information from the input unit 310. For example, when the operator selects at least one target candidate output from the display unit 320 or inputs a filter condition, the operation unit 160 receives the operation information from the input unit 310.

  Next, the target detection support method will be described with reference to FIGS. The target detection support method is executed by the target detection support system 100. FIG. 2 is a flowchart illustrating an example of the target detection support method. FIG. 3 is a chart showing object information and target candidate information. FIG. 3A is a chart showing information on the object acquired by the communication information processing unit 147 based on the detection information at the detection time T0. FIG. 3B is acquired by the radar information processing unit 142, the light wave information processing unit 143, the reverse detection information processing unit 144, the magnetic information processing unit 145, and the ship identification information processing unit 146 based on the detection information at the detection time T1. It is the chart showing the information of the target object. FIG. 3C is a chart showing information on the object obtained by the acoustic information processing unit 141 based on the detection information at the detection time T2. FIG. 3D is a chart showing marine information. FIG. 3E is a chart showing the result of analyzing the target candidate information at the detection time T2. 3B and 3C represent the position of the object, the direction of the bar mark extending from the circle mark represents the course of the object, and the length of the bar mark is the speed of the object. Represents. A triangular mark in FIG. 3C represents the receiver D of the passive acoustic sensor 210. In the following description, since the detection times of the sensors 200 are different from each other, sensor information at different detection times T0, T1, and T2 is used. However, sensor information at the same detection time can also be used.

  When the target detection support method is started, the acquisition unit 130 acquires sensor information from the sensor 200 (step S11). And the acquisition part 130 outputs sensor information to the detection information processing part 140 corresponding to the sensor 200 based on sensor identification information. This sensor information includes detection information of the sensor 200, detection time information thereof, sensor identification information, and sensor position information.

  The detection information processing unit 140 acquires information on the object from the sensor information (step S12). Information about this object is acquired for each sensor 200. However, not all the sensors 200 need to detect the object. One sensor 200 may detect a plurality of objects. When there are a plurality of objects, each sensor 200 may not detect all the objects.

  For example, when the communication device 270 obtains information about the underwater vehicle, information on the underwater vehicle that is the target is set based on the sensor information from the communication device 270 in order to set a range for detecting the target. Acquired by the communication information processing unit 147. The sensor information includes the detection time T0, the position, size, speed, and course of the underwater vehicle.

  First, as shown in FIG. 3A, the communication information processing unit 147 obtains the position and size of the underwater vehicle as the position and size of the object a1. Further, the communication information processing unit 147 obtains the position prediction range a2 of the object a1 at the time T2 from the detection time T0 of the underwater vehicle, the position, speed, and course of the object a1. Then, a range including the object a1 and the position prediction range a2 is set as the detection range of the target detection support system 100.

  Next, information on an object in the detection range at the detection time T <b> 1 is acquired based on sensor information from other sensors 200. For example, as illustrated in FIG. 3B, the radar information processing unit 142 obtains the position, speed, and course of the object b1 at time T1 from the sensor information of the radar sensor 220. Further, the position of the object b1 at time T2 is estimated from these pieces of information.

  The light wave information processing unit 143 obtains the position of the object b2 at time T1 from the sensor information of the light wave sensor 230. However, the object b2 is not detected at the time of detection immediately after the detection at time T1. For this reason, this information that it was not detected is also obtained as information on the object b2, and for example, in FIG. 3B, a circle mark indicating the position of the object b2 is represented by a broken line.

  Further, the reverse detection information processing unit 144 obtains the position, speed, and course of the object b3 at time T1 from the sensor information of the reverse detection device 240, and further estimates the position of the object b3 at time T2 from this information. In addition, the magnetic information processing unit 145 obtains the position of the object b4 at time T1 from the sensor information of the magnetic detection device 250. The ship identification information processing unit 146 obtains the position, speed, and course of the object b5 at time T1 from the sensor information of the automatic ship identification device 260, and further estimates the position of the object b5 at time T2 from this information. .

  Next, information on the object in the detection range at the detection time T <b> 2 is acquired based on sensor information from other sensors 200. For example, as shown in FIG. 3C, the acoustic information processing unit 141 obtains the positions of the objects c1 and c2 at time T2 from the sensor information of the active acoustic sensor 210. In addition, the acoustic information processing unit 141 obtains the positions, speeds, and courses of the objects c3 to c6 at the time T2 from the sensor information of the passive acoustic sensor 210.

  The generation unit 151 of the target information processing unit generates target candidate information from the object information (step S13). At this time, the generation unit 151 acquires marine information in the detection range from the storage unit 120 and refers to it. For example, as shown in FIG. 3D, information on seamounts d1, shoals d2, and shipwrecks d3 in the detection range is obtained.

  As shown in FIGS. 3A to 3C, a plurality of objects are detected by various sensors 200 in the detection range, and a plurality of pieces of information are acquired for one object. For this reason, the objects of the various sensors 200 are associated with each other based on the detection time and the position of the object, and information about each object is collected into one and generated as target candidate information. In addition, when only one information is acquired about one target object, the information of the target object is produced | generated as target candidate information.

  For example, since the estimated position of the target object b1 at time T2 and the detected position of the target object c3 at time T2 match or approximate, the information on the target object b1 and the information on the target object c3 are collected together as the first target candidate. Generate as information. Since there is no other object that matches or approximates the position of the object b2, information on the object b2 is generated as information on the second target candidate. Similarly, the information on the object b3 and the information on the object c5 are collectively generated as information on the third target candidate. The information on the object b4, the information on the object c1, and the information on the ship wreck d3 are collectively generated as information on the fourth target candidate. The information on the target object b5 and the information on the target object c4 are collectively generated as the information on the fifth target candidate. The information on the object c2 and the information on the seamount d1 are collectively generated as information on the sixth target candidate. Information on the object c6 is generated as information on the seventh target candidate.

  In order to analyze the target candidate information using a filter, the receiving unit 160 receives the filter condition (operation information) input by the operator from the input unit 310 and outputs it to the target candidate information processing unit 150 (step S14). For example, when detecting an underwater vehicle, the operator inputs a feature amount of the target such as the speed and size of the underwater vehicle to be detected as a filter condition.

  The analysis unit 152 analyzes the information of each target candidate by multivariate analysis using a predetermined filter based on the filter condition (step S15). When the output unit 153 outputs the analysis result to the display unit 320 (step S16), for example, as shown in FIG. 3E, the analysis result of the target candidate is graphically displayed on the display unit 320. As a result of this analysis, in addition to the position of the target candidate extracted from the analysis, a feature relating to information on each target candidate is output. As a feature related to the target candidate information, there is a type of the target candidate to be estimated. In FIG. 3E, the type of surface ship is indicated by a square mark. Moreover, it is shown with a star mark as a thing with high possibility of a target object based on the conditions of a filter. In addition, as a feature related to information on other target candidates, information that the target b2 in FIG. 3B is detected once but not detected as in the information on the second target candidate, and the target candidate is not detected thereafter. Information that a plurality of sensors 200 are detected, and information that a target candidate is detected only by one sensor 200 may be output.

  For example, the first target candidate is detected by the acoustic sensor 210 and the radar sensor 220 and, as shown in FIG. 3 (e), is estimated to be a surface ship e1 by a square mark, as indicated by a square mark. It is displayed. Similarly, the third target candidate is assumed to be a surface vessel e2, and the fifth target candidate is assumed to be a surface vessel e3, and is displayed with a square mark. Further, since the second target candidate is not detected after being detected by the light wave sensor 230 at time T1, it is not displayed as the analysis result. Since the fourth target candidate includes marine information of the shipwreck d3 as target candidate information, it is estimated as the shipwreck d3 and is not displayed as the analysis result. Similarly, the sixth target candidate is estimated as seamount d1 and is not displayed in the analysis result. In addition, the seventh target candidate is detected by the passive acoustic sensor 210, but is not displayed as a non-estimated object e4 because there is no information on the other sensors 200 and the like. The course of the unestimated object e4 is represented by the direction of the bar mark extending from the star mark, and the speed of the unestimated object e4 is represented by the length of the bar mark.

  When the operator looks at the analysis result and selects an object from the four first, third, fifth, and seventh target candidates and inputs the selection using the input unit 310, the accepting unit 160 receives the selection (operation information). Accept and output to the target candidate information processing unit 150 (step S17). For example, when the operator selects the unestimated object e4, the analysis unit 152 of the target candidate information processing unit 150 extracts information on the seventh target candidate corresponding to the unestimated object e4. Thereby, the seventh target candidate is determined as a target to be detected (step S18).

  In this embodiment, four target candidates are extracted as analysis results, but the analysis results may be zero or one target candidate. One target candidate is selected as the target, but a plurality of targets may be selected.

  According to the above configuration, the analysis result of the target candidate information is output, and at least one selection from the target candidates is accepted. In this way, for an underwater target that is difficult to detect whether or not it exists, the operator can flexibly determine the output target candidate information and select a target from the target candidates. . For this reason, the target in water can be found more accurately.

  Further, not only the position of the target candidate but also a feature related to the target candidate information is output. For this reason, the operator can determine a target candidate based on various information, and can find the target in water more accurately.

  Furthermore, target candidate information is generated based on detection information of the acoustic sensor 210 that can detect a wide range of underwater. Thereby, the target in water can be detected in a wider range.

(Embodiment 2)
FIG. 4 is a flowchart showing an example of the target detection support method of the target detection support system 100 according to the second embodiment. Also in the flow shown in FIG. 4, the processing of each step shown in FIG. 2 is executed. However, in the flow shown in FIG. 4, a process of determining whether or not a target is determined (step S19) is executed between the process of step S16 and the process of step S17. The accepting unit 160 accepts resetting of filter conditions before accepting selection from the target candidates.

  For example, if the operator cannot select a target from among the target candidates, the operator can select the target without selecting the target candidate in order to reset the filter conditions and analyze the target candidate information again. An unselected candidate is input by the input unit 310. When the unselected (operation information) is received by the receiving unit 160 from the input unit 310 (step S19: NO), the process returns to step S14 in order to reset the filter conditions. Then, the receiving unit 160 receives again the filter condition (operation information) from the input unit 310 (step S14). Based on the new filter condition, the target candidate information processing unit 150 reanalyzes the target candidate information (step S15) and outputs the reanalysis result (step S16). If the operator cannot select a new target candidate in the reanalysis result (step S19: NO), the processes of S14 to S16 and S19 are repeated. On the other hand, if the target candidate is selected by the operator (step S19: YES, S17), the selected target candidate is determined as a target (step S18).

  By executing the target detection support method, the filter condition is reset and the target candidate information is reanalyzed. Therefore, the operator can flexibly determine the analysis result and set a more appropriate filter condition according to the target, so that the target in water can be found more accurately.

(Embodiment 3)
FIG. 5 is a block diagram showing a main configuration of target detection support system 100 according to the third embodiment. As shown in FIG. 5, the target detection support system 100 according to Embodiment 3 further includes a control unit 170. For example, when tracking the target determined by the target candidate information processing unit 150, the control unit 170 obtains a parameter (control parameter) for controlling the sensor 200 so as to detect the target more accurately. Output to.

  FIG. 6 is a flowchart illustrating an example of the target detection support method of the target detection support system 100 according to the third embodiment. Also in the flow shown in FIG. 6, the processing of each step shown in FIG. 4 is executed. However, in the flow shown in FIG. 6, after the process of step S18, a control parameter is acquired, and a process (steps S10 to S13) of controlling the sensor 200 with the control parameter is executed.

  Specifically, when the target is determined (step S18), the target information processing unit outputs information on the target to the control unit 170. The control unit 170 acquires a control parameter based on the target information (step S20).

  For example, when the control unit 170 controls the active acoustic sensor 210 having a plurality of transmitters and a plurality of receivers, the control unit 170 selects a transmitter according to the position of the target and the course. At this time, a transmitter capable of transmitting the sound wave so that the sound wave reflected from the target can be easily received by the receiver is selected, and the control parameter of the acoustic sensor 210 that transmits the sound wave is acquired from the transmitter. To do.

  When controlling the radar sensor 220 having a plurality of detection modes, the detection mode is selected according to the size of the target. For example, when the size of the target is small, a mode for detecting a small target is set as the control parameter of the radar sensor 220.

  Further, when controlling the light wave sensor 230 capable of detecting a plurality of types of light rays, the detection light rays are selected according to the position of the target. For example, if there is a target during the day when sunlight is incident, the control parameter is used to detect sunlight. Further, if there is a target at night, it is set as a control parameter for detecting infrared rays.

  The control unit 170 outputs the control parameter to the display unit 320 (step S20). Thereby, the operator examines whether or not the control parameter displayed on the display unit 320 is appropriate, and inputs the examination result (operation information) through the input unit 310. The receiving unit 160 receives the operation information and outputs it to the control unit 170 (step S21). If it is determined that the control parameter is valid, the control unit 170 receives the approval of the control parameter (steps S21, S22, YES), and outputs the control parameter to the sensor 200 that controls the control parameter. Thereby, the sensor 200 is controlled by the control parameter (step S23).

  On the other hand, if it is determined that the control parameter is not valid, the control unit 170 receives non-approval of the control parameter (steps S21, S22, NO), returns to the process of step S20, and acquires the control parameter again. If the control parameter is not approved (NO in step S22), the control parameter may be continuously used for the control parameter before acquisition (step S20) without acquiring the control parameter again.

  According to the above configuration, the target can be detected more accurately by the sensor 200 by setting the control parameters of the sensor 200 according to the target. For this reason, tracking of the determined target can be continued.

(Embodiment 4)
FIG. 7 is a block diagram illustrating a partial configuration of the target detection support system 100 according to the fourth embodiment. As shown in FIG. 7, in the target detection support system 100 according to Embodiment 4, the acoustic sensor 210 includes a plurality of transmitters 1 and a plurality of receivers 2. The acoustic information processing unit 141 includes an extension detection region generation unit 14, a weight setting unit 18, a vote addition unit 19, and an existence region specification unit 20. Note that, for example, the object position detection device of Japanese Patent Application No. 2013-225124 can be applied to the acoustic information processing unit 141 shown in FIG. In this case, the voting adder 19 sets the number of votes corresponding to the extended detection area 15 generated by the extended detection area generation section 14 in consideration of the weighting set by the weighting setting section 18 and the presence area specifying section 20. Identifies the area where the number of votes is high to determine the position of the object. However, the method for obtaining the position of the object is not limited to this, and other known methods can be used.

  The acoustic sensor 210 outputs sensor information to the acoustic information processing unit 141 via the acquisition unit 130 when the transmitter 1 transmits the sound wave and the wave receiver 2 receives the sound wave reflected by the object. The sensor information includes detection symbol information (detection information), sensor identification information, and observation error information. The detected symbol information includes, for example, transmission time, reception time, received signal strength, and the like. The sensor identification information includes transmitter identification information and receiver identification information. In the storage unit 120 of the target detection support system 100, the transmitter identification information is associated with the position of the transmitter 1, and the receiver identification information is associated with the position and directivity of the receiver 2. It has been. The observation error information includes a reception azimuth error based on the sensitivity characteristic of the receiver 2 and a propagation distance error based on the time resolution characteristic of the receiver 2.

  Since the detection by the sensor 200 includes an error, the extended detection area generation unit 14 generates an extended detection area 15 in consideration of this error based on the sensor information. The extended detection area 15 is an area obtained by extending the detection error range (error distribution) of the sensor 200 based on the observation error information from the position (target detection position) 7 of the target obtained based on the detection information. In this area, there is a possibility that an object exists.

  Specifically, as illustrated in FIG. 8, the extended detection region generation unit 14 refers to the storage unit 120 to determine the position of the transmitter 1, the receiver 2 from the transmitter identification information and the receiver identification information. And the directivity of the receiver 2 are obtained. The detection position 7 of the object detected by the sensor 200 is specified by these information and the time difference between the transmission time and the reception time of the detected symbol information. Next, an ellipse having a reception azimuth error 16 in the length of the major axis and a propagation distance error 17 in the length of the minor axis around the detection position 7 of the object is generated as the extended detection region 15.

  The weighting setting unit 18 weights the number of votes based on the sensor information. Specifically, as shown in FIG. 9, when a sound wave is transmitted from one transmitter 1 and a reflected wave of this sound wave is received by two wave receivers 2, a plurality of detection positions 7 are detected. Is done. Here, when there is one object reflecting the sound wave, each of the two receivers 2 receives one sound wave. Thereby, one detection position 7 is specified for one receiver 2. However, there are a large number of objects other than the object in the water, and the wave receiver 2 receives a plurality of noises for one sound wave together with the reflected waves from them. For this reason, a large number of detection positions 7 are detected for the two receivers 2. The virtual ellipse 5 is an ellipse drawn by the time difference between the transmission time of the sound wave and the reception time of the sound wave reflected from the object, the position of the transmitter 1 and the position of the receiver 2. It can be assumed that an object exists on the virtual ellipse 5.

  An extended detection area 15 is generated around each of the plurality of detection positions 7 detected in this way, and an area where the object is located is specified from these extended detection areas 15. In this case, if the extended detection areas 15 are overlapped and the overlapping extended detection areas 15 are detected by different receivers 2, there is a possibility that an object exists in the overlapping portion. high. Therefore, first, the weight of the non-overlapping extension detection area 15 is set smaller than the weight of the overlapping extension detection area 15, for example, 0. Next, for a plurality of overlapping extended detection areas 15, it is determined whether or not they are extended detection areas 15 by the same receiver 2 based on the receiver identification information of the sensor information. As a result, if the overlapped extended detection areas 15 are from different receivers 2, it is highly possible that an object is present in the overlapping portion, and the extended detection areas 15 overlapped by the same receiver 2 are assumed. Set a larger weight.

  It should be noted that whether or not the extended detection area 15 is the same receiver 2 is determined by the probability of a BIT process, a normal distribution, or the like in which points (detection points) in the extended detection area 15 are represented by the ID code of the receiver 2. This is performed by a process of multiplying the density distribution for each detection point.

  Further, the weighting setting unit 18 may correct the weighting based on the intensity of the received signal of the receiver 2 and / or the distance between the receiver 2 and the extended detection region 15. For example, when the intensity of the received signal of the receiver 2 is smaller than a predetermined value, the weighting is reduced. When the distance between the detection position 7 of the object in the extended detection area 15 and the receiver 2 is shorter than the lower limit predetermined value or longer than the upper limit predetermined value, the weighting is reduced.

  The vote adding unit 19 sets the number of votes corresponding to the extended detection area 15 in the voting space 23 in consideration of weighting. Specifically, as shown in FIG. 10, a plurality of cells (ballot boxes) 22 are two-dimensionally arranged in a net shape in the voting space 23. The number of votes corresponding to the four extended detection areas 15 (15A, 15B, 15C, 15D) in consideration of weighting is set in the ballot box 22. Note that the three-dimensional voting space 23 may be provided by arranging the voting boxes 22 in three dimensions. In this case, the ballot box 22 is set with the number of votes corresponding to the ellipsoid-shaped extension detection region 15 obtained by extending the ellipse in three dimensions.

  When voting on this ballot box 22, the number of votes is determined by weighting and the position of the extended detection area 15. First, the weighting is set to 0 for the extended detection areas 15 that do not overlap. For this reason, the voting box 22 at the position of the extended detection area 15 that does not overlap is not voted, or 0 votes are cast.

  Next, the number of votes corresponding to the weight is set in the ballot box 22 in the overlapping extension detection area 15. This weighting is determined by the weighting setting unit 18 based on whether or not the extended detection region 15 is from the same receiver 2. In the following description, the receiver 2 is determined based on the orientation of the major axis of the extension detection region 15 and the ratio of the area of the overlapping portion with respect to the extension detection region 15. However, the present invention is not limited to this. It is also determined by the identification information of the waver 2. In addition, the intensity of the received signal defining the detection position 7 in the extended detection areas 15A, 15B, 15C, 15D is the same or substantially the same. Further, since the extended detection areas 15A, 15B, 15C, and 15D are close to each other, the distances between the detection positions 7 in the extended detection areas 15A, 15B, 15C, and 15D and the receiver 2 are substantially equal. Therefore, it is assumed that weighting correction based on the strength of the received signal and the distance between the detection position 7 and the receiver 2 has not been made.

  The extension detection area 15A overlaps the extension detection area 15B. Most of the extended detection areas 15A and 15B overlap, and the directions of the major axes of the extended detection areas 15A and 15B are the same or approximate. Therefore, since it can be determined that each of the extended detection areas 15A and 15B is based on the same receiver 2, the weight is set to 1. Therefore, the vote adding unit 19 sets the number of votes 1 based on the weight 1 and the basic vote 1 to the ballot box 22 in the range where only the extension detection area 15A and the extension detection area 15B overlap. Since the extended detection areas 15C and 15D are the same as the extended detection areas 15A and 15B, the number of votes is set to 1 in the ballot box 22 where only the extended detection area 15C and the extended detection area 15D overlap. .

  Further, the extension detection area 15A also overlaps with the extension detection area 15C. This overlapping range is smaller than the overlapping range of the extension detection areas 15A and 15B, and the orientation of the major axis of the extension detection area 15A does not match the orientation of the major axis of the extension detection area 15C. Therefore, since it can be determined that each of the extended detection areas 15A and 15C is based on a different receiver 2, the weighting is set large. In this case, since the two extended detection areas 15 overlap, the weight is not simply set to 2, but is set to a larger value, for example, 3. Therefore, the vote adding unit 19 sets the number of votes 3 based on the weight 3 and the basic vote 1 in the ballot box 22 in the range where the extension detection area 15A and the extension detection area 15C overlap. Note that the overlapping range of the extended detection areas 15A and 15D, the overlapping range of the extended detection areas 15B and 15C, and the overlapping range of the extended detection areas 15B and 15D are similar to the overlapping range of the extended detection areas 15A and 15C. The number of votes 3 is set in the ballot box 22.

  The voting adder 19 can also consider Doppler information for the detection position 7 that defines the expanded detection region 15 when reflecting the expanded detection region 15 in the voting space 23. Based on this Doppler information, the speed at which the object moves inward or outward of the virtual ellipse 5 is obtained. For this reason, the detection position 7 and the extended detection area 15 based on the detection position 7 can be derived more accurately according to the speed of the object. The Doppler information obtained from a certain receiver 2 can be used to specify the detection position 7 obtained from another receiver 2.

  The existence area specifying unit 20 specifies an area having a high number of votes in the voting space 23 as the object existence area 24 of the target object. In the case illustrated in FIG. 10, an area where the ballot box 22 having three votes is set as the object existence area 24 of the target object.

  Next, the target detection support method will be described with reference to FIG. FIG. 11 is a flowchart illustrating an example of the target detection support method of the target detection support system 100 according to the fourth embodiment. As illustrated in FIG. 11, the extended detection area generation unit 14 acquires sensor information including detection symbol information from the acoustic sensor 210 (step S1). The extended detection area generation unit 14 generates an extended detection area 15 based on the sensor information (step S2). The weighting setting unit 18 determines whether or not the overlapping extension detection regions 15 are from the same receiver 2 based on the direction of the extension detection region 15 and the receiver identification information of the sensor information. Based on the determination result, the weighting in the range where the extension detection areas 15 overlap is set (step S3). The voting adder 19 sets the number of votes corresponding to the extended detection area 15 in the voting space 23 in consideration of weighting (step S4). Here, the processes in steps S1 to S4 described above are repeated by the number of detected symbol information, that is, the number of extended detection areas 15. Then, the existence area specifying unit 20 specifies an area having a large number of votes in the voting space 23 (step S5). The acoustic information processing unit 141 outputs the identified region to the target candidate information processing unit 150 as the existence region (position) 24 of the target object (step S6).

  According to the above configuration, the position of the object can be detected quickly and accurately by weighting based on the difference between the receivers 2. In addition, the operator can more flexibly detect the position of the object according to the operator's judgment by determining the factors for correcting the weighting (the intensity of the received signal, the distance between the detection position 7 and the receiver 2, etc.). it can.

  In addition, the position of the object is output as an area having a spread instead of a point. Therefore, the association with the information of the object by the other sensor 200 is facilitated, and the information of the target candidate can be generated with higher accuracy.

(Embodiment 5)
FIG. 12 is a block diagram illustrating a main configuration of target detection support system 100 according to the fifth embodiment. As shown in FIG. 12, the target detection support system 100 according to Embodiment 5 further includes a detection information storage unit 180. Note that the detection information storage unit 180 according to the fifth embodiment may be provided in the configuration of the target detection support system 100 according to the other first to fourth embodiments.

  The acquisition unit 130 outputs sensor information from the various sensors 200 to the detection information processing unit 140 corresponding to the sensor identification information. The detection information processing unit 140 generates information on the object based on the sensor information and stores the sensor information in the detection information storage unit 180. Note that the acquisition unit 130 may output the sensor information to the detection information processing unit 140 and store the sensor information in the detection information storage unit 180. In addition, it is not necessary to store all of the sensor information in the detection information storage unit 180. For example, detection information and sensor position information may be stored without storing sensor identification information.

  The detection information storage unit 180 stores detection information from the sensor 200. The detection information storage unit 180 includes, for example, an acoustic information storage unit 181, a radar information storage unit 182, a light wave information storage unit 183, a reverse detection information storage unit 184, a magnetic information storage unit 185, a ship identification information storage unit 186, and a communication information storage. The unit 187 and the enemy teammate information storage unit 188 are configured. One detection information storage unit 180 is provided corresponding to one sensor 200. However, one detection information storage unit 180 may be provided for the plurality of sensors 200. The detection information storage unit 180 is provided separately from the storage unit 120, but may be provided integrally with the storage unit 120.

  FIG. 13 is a flowchart illustrating an example of the target detection support method of the target detection support system 100 according to the fifth embodiment. Also in the flow shown in FIG. 13, the processing of each step shown in FIG. 4 is executed. However, in the flow shown in FIG. 13, after the process of step S <b> 18, the determined target is tracked, and when the tracking cannot be performed, the process of regenerating target information (steps S <b> 30 to S <b> 34) is executed. In the flow shown in FIG. 13, the process in step S19 may be omitted as in FIG. Further, in the flow shown in FIG. 13, the processes of steps S20 to S23 shown in FIG. 6 may be executed between steps S30 and S32.

  Specifically, when the target is determined (step S18), the generation unit 151 generates information related to the target from various sensor information and tracks the target (step S30). The output unit 153 outputs information about the target and displays it on the display unit 320, so that the operator can monitor the target based on the information.

  While the target is being tracked (step S31: NO), if the generation unit 151 cannot generate information on the target, the target cannot be tracked (step S32: NO). Proceed to processing. Here, in order to regenerate information related to the target from the past sensor information, the operator sets a condition (regeneration condition) for regenerating the target information using the input unit 310. Thereby, the reception unit 160 receives the regeneration condition from the input unit 310 (step S33). Examples of the regeneration condition include a detection time (call value) of detection information to be read and a condition (adjustment value) for processing the detection information. Examples of the adjustment value include weights set by the weight setting unit 18 (FIG. 7) according to the fourth embodiment.

  The detection information processing unit 140 receives the regeneration condition from the reception unit 160, and reads the detection information from the detection information storage unit 180 according to the call value of the regeneration condition (step S34). At this time, sensor identification information, sensor position information, and the like may be read out together with the detection information. Then, the detection information processing unit 140 acquires the information on the target object again based on the read information and the adjustment value (Step S12). For example, when the adjustment value is weighting of the acoustic sensor 210, the number of votes corresponding to the extended detection area 15 (FIG. 10) is set in the voting space 23 (FIG. 10) according to the newly set weighting, and the object having a large number of votes The existence area 24 (FIG. 10) is acquired as the position of the object. Thus, based on the position of the newly acquired object, target candidate information is generated and analyzed (steps S13 to S15), and the analysis result is output to the display unit 320. As a result, the operator can determine target candidates and targets by looking at past information.

  According to the above-described embodiment, the information on the object can be regenerated from the detection information of the various sensors 200 by receiving the regeneration condition from the operator. Based on the information on the regenerated object, new target candidate information reflecting the operator's judgment can be generated and provided to the operator. As described above, since the operator's judgment material increases, the target can be detected with higher accuracy.

  Note that all the above embodiments may be combined with each other as long as they do not exclude each other.

  From the foregoing description, many modifications and other embodiments of the present invention are obvious to one skilled in the art. Accordingly, the foregoing description should be construed as illustrative only and is provided for the purpose of teaching those skilled in the art the best mode of carrying out the invention. The details of the structure and / or function may be substantially changed without departing from the spirit of the invention.

  The target detection support system 100 and the method thereof according to the present invention are useful as the target detection support system 100 and the method thereof that can find a target in water with higher accuracy.

DESCRIPTION OF SYMBOLS 14 Extended detection area production | generation part 15, 15A, 15B, 15C, 15D Extended detection area 16 Reception azimuth | direction error 17 Propagation distance error 19 Vote addition part 20 Existence area specific | specification part 100 Target detection assistance system 140-148 Detection information processing part (processing part) )
151 Generating Unit 152 Analyzing Unit 153 Output Unit 160 Receiving Unit 170 Control Unit 180-188 Detection Information Storage Unit 200 Sensor

Claims (7)

A system that supports the detection of targets in the water,
A processing unit for acquiring detection information of an object detected by each of a plurality of types of sensors;
A generating unit that generates target candidate information based on the detection information;
An analysis unit that analyzes the target candidate information using a predetermined filter;
An output unit for outputting the result of the analysis;
A target detection support system comprising: a reception unit that receives a selection from the target candidates.   The target detection support system according to claim 1, wherein the reception unit receives resetting of the filter condition before receiving selection from the target candidates.   The target detection support system according to claim 1, further comprising a control unit that creates a parameter for controlling the sensor based on the selected target candidate information. A storage unit for storing the detection information;
After receiving a selection from among the target candidates, when the receiving unit receives a regeneration condition for the information on the target candidate, the generation unit reads the detection read from the storage unit according to the regeneration condition The target detection support system according to any one of claims 1 to 3, wherein the target candidate information is regenerated based on the information.   The target detection support system according to any one of claims 1 to 4, wherein the output unit outputs characteristics related to the target candidate information together with the position of the target candidate. The sensor includes an acoustic sensor including a transmitter and a plurality of receivers;
The processor is
An extended detection region generating unit that acquires the detection information and observation error information from the acoustic sensor, and generates an extended detection region in which an error distribution based on the observation error information is reflected at a position of an object based on the detection information When,
A vote adding unit that sets the number of votes corresponding to the extended detection area in a voting space;
6. The target detection support system according to claim 1, further comprising: an area specifying unit that specifies an area with a large number of votes as an existence area of the object in the voting space. A target detection support method for supporting detection of a target in water,
Obtaining detection information of objects detected by each of multiple types of sensors,
Generating target candidate information based on the detection information;
Output the result of analyzing the target candidate information using a predetermined filter,
A target detection support method for receiving a selection from the target candidates.

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