Vessel detection device, vessel detection system, and vessel detection method

Abstract

Provided is a watercraft detection device etc. that can detect a waterfcraft. A watercraft detection device (2) comprises: a motion detection means (21) that detects the motion of an object on the water and the motion of waves in the water surface surrounding the object, on the basis of laser light emitted onto the object and onto the water surface, and on the basis of reflected light corresponding to the laser light; and a watercraft detection means (22) that detects a watercraft by determining whether the object is a watercraft or not, on the basis of the motion of the object and the motion of the waves.

Description

[Technical field]

[0001] The present invention relates to a marine vessel detection device that detects a marine vessel, and more particularly to a marine vessel detection device that detects a marine vessel using LiDAR (Light Detection and Ranging). [Background technology]

[0002] Patent Document 1 discloses a technique for measuring the direction and speed of waves around an unmanned marine vehicle using a laser radar mounted on the unmanned marine vehicle.

[0003] As related art, the techniques described in Patent Documents 2 and 3 are also known. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2017-058322 A [Patent Document 2] JP 2005-096674 A [Patent Document 3] JP 2009-031188 A Summary of the Invention [Problem to be solved by the invention]

[0005] The technology described in Patent Document 1 measures the direction and speed of waves around the unmanned marine vehicle, but does not detect other vessels (such as suspicious ships) around the unmanned marine vehicle. Therefore, there is a problem in that the technology described in Patent Document 1 cannot detect vessels.

[0006] In view of the above-mentioned problems, an object of the present invention is to provide a marine vessel detection device and the like capable of detecting a marine vessel. [Means for solving the problem]

[0007] The marine vessel detection device of the present invention comprises a motion detection means which detects the movement of an object and the movement of waves on the water surface based on laser light irradiated onto an object on the water and the water surface surrounding the object, and reflected light corresponding to the laser light, and a marine vessel detection means which detects the object by determining whether or not the object is a marine vessel based on the movement of the object and the movement of the waves.

[0008] The marine vessel detection system of the present invention comprises a motion detection means which detects the movement of an object and the movement of waves on the water surface based on laser light irradiated onto an object on the water and the water surface surrounding the object, and reflected light corresponding to the laser light, and a marine vessel detection means which detects the object by determining whether or not the object is a marine vessel based on the movement of the object and the movement of the waves.

[0009] In the marine vessel detection method of the present invention, a motion detection means detects the movement of an object and the movement of waves on the water surface based on laser light irradiated onto the object on the water and the water surface surrounding the object, and reflected light corresponding to the laser light, and a marine vessel detection means detects the marine vessel by determining whether or not the object is a marine vessel based on the movement of the object and the movement of the waves. Effect of the Invention

[0010] According to the present invention, it is possible to detect a navigation body. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing a main part of a marine object detection system according to a first embodiment. [Diagram 2] FIG. 2 is a block diagram showing a main part of each LiDAR device in the underwater vehicle detection system according to the first embodiment. [Diagram 3] FIG. 3 is a block diagram showing a main part of the underwater vehicle detection device according to the first embodiment. [Figure 4] FIG. 4 is a block diagram showing a main part of a motion detection unit in the underwater vehicle detection device according to the first embodiment. [Diagram 5] FIG. 5 is a block diagram showing a hardware configuration of a main part of the underwater vehicle detection device according to the first embodiment. [Figure 6] FIG. 6 is a block diagram showing another hardware configuration of the main parts of the underwater vehicle detection device according to the first embodiment. [Figure 7] FIG. 7 is a block diagram showing another hardware configuration of the main parts of the underwater vehicle detection device according to the first embodiment. [Figure 8] FIG. 8 is a flowchart showing the operation of the marine object detection device according to the first embodiment. [Figure 9] FIG. 9 is an explanatory diagram showing an example of a state in which the water surface and objects within the target area are irradiated with laser light. [Figure 10] FIG. 10 is an explanatory diagram showing an example of a velocity vector corresponding to the motion of waves and a velocity vector corresponding to the motion of an object. [Figure 11] FIG. 11 is an explanatory diagram showing an example of a state in which a velocity vector corresponding to the motion of an object is decomposed into a parallel component and a perpendicular component with respect to a velocity vector corresponding to the motion of waves. [Figure 12] FIG. 12 is a block diagram showing a main part of another marine vessel detection device according to the first embodiment. [Figure 13] FIG. 13 is a block diagram showing a main part of another marine vessel detection system according to the first embodiment. [Figure 14] FIG. 14 is a block diagram showing a main part of the underwater vehicle detection system according to the second embodiment. [Figure 15] FIG. 15 is a block diagram showing a main part of a marine object detection device according to the second embodiment. [Figure 16] FIG. 16 is a block diagram showing a main part of a motion detection unit in a marine vessel detection device according to the second embodiment. [Figure 17] FIG. 17 is a flowchart showing the operation of the marine vessel detection device according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0013] [First embodiment] Fig. 1 is a block diagram showing a main part of the underwater vehicle detection system according to the first embodiment. Fig. 2 is a block diagram showing a main part of each LiDAR device in the underwater vehicle detection system according to the first embodiment. Fig. 3 is a block diagram showing a main part of the underwater vehicle detection device according to the first embodiment. The underwater vehicle detection system according to the first embodiment will be described with reference to Figs. 1 to 3.

[0014] 1, the underwater body detection system 100 includes N LiDAR devices 1_1 to 1_N, where N is an integer equal to or greater than 1. In other words, the underwater body detection system 100 includes at least one LiDAR device 1. Specifically, for example, the underwater body detection system 100 includes one, two, or three LiDAR devices 1.

[0015] Each LiDAR device 1 is installed so as to emit laser light toward an area (hereinafter referred to as a "target area") A to be detected by a vessel (e.g., a ship, a jet ski, a rubber boat, a submarine, etc.). Here, the vessel is a moving body having a power. The vessel may include a suspicious vessel. Here, a suspicious vessel refers to a vessel that should not be present in the target area A. In the following description, a suspicious vessel may be called a suspicious ship. Usually, the target area A is a predetermined area in a predetermined sea area. Each LiDAR device 1 is installed, for example, on land around the target area A, on a ship navigating around the target area A, on a ship navigating inside the target area A, or on an aircraft (more specifically, an aircraft, a drone, etc.) flying above the target area A. A drone is an unmanned aerial vehicle that can be remotely controlled or fly autonomously, and is also known as a UAV (Unmanned Aerial Vehicle) or UAS (Unmanned Aerial System).

[0016] As shown in FIG. 2, each LiDAR device 1 includes an emitter 11 and a light receiver 12. The emitter 11 emits laser light to a target area A. The emitted laser light is irradiated to an object O on the water (e.g., on the sea) in the target area A. The emitted laser light is also irradiated to the water surface (e.g., the sea surface) in the target area A. In other words, the emitted laser light is irradiated to the water surface (e.g., the sea surface) around the object O. The irradiated laser light is reflected as scattered light. The light receiver 12 receives backscattered light of the reflected scattered light. Hereinafter, the light received by the light receiver 12 may be referred to as "reflected light". In other words, the reflected light received by the light receiver 12 corresponds to the laser light emitted by the emitter 11.

[0017] The object O may include a floating object on the water surface (for example, the sea surface) in the target area A. The object O may also include a vessel navigating within the target area A.

[0018] Here, in each LiDAR device 1, the direction of emission of the laser light by the emission unit 11 is variable. As a result, the emission unit 11 emits the laser light in each of a plurality of directions that are different from each other. As a result, the laser light is irradiated so as to scan the target area A. In other words, the laser light is irradiated so as to scan the target area A.

[0019] 1, the marine vessel detection system 100 includes a marine vessel detection device 2 and an output device 3. As shown in FIG 3, the marine vessel detection device 2 includes a motion detection unit 21, a marine vessel detection unit 22, a suspicious vessel detection unit 23, and a notification control unit 24.

[0020] The motion detection unit 21 detects the motion of ocean waves W in the target area A and the motion of each object O in the target area A based on the laser light emitted by each LiDAR device 1 and the reflected light received by each LiDAR device 1. As shown in FIG. 4 , the motion detection unit 21 includes a distance calculation unit 31, a three-dimensional model generation unit 32, and a velocity vector calculation unit 33.

[0021] That is, the motion detection unit 21 acquires information on each LiDAR device 1, information on the laser light emitted by each LiDAR device 1, and information on the reflected light received by each LiDAR device 1. Hereinafter, these pieces of information may be collectively referred to as "LiDAR information." The LiDAR information is acquired from each LiDAR device 1 through communication between the marine vessel detection device 2 and each LiDAR device 1.

[0022] The distance calculation unit 31 uses predetermined information included in the LiDAR information to calculate a distance D between a point where each LiDAR device 1 is installed and a point where the laser light emitted in each direction by the corresponding LiDAR device 1 is reflected by the water surface or an object O. The calculation of the distance D is performed, for example, by a ToF (Time of Flight) method or an FMCW (Frequency Modulated Continuous Wave) method.

[0023] When the ToF method is used, each LiDAR device 1 emits a pulsed laser light. The LiDAR information includes information indicating the timing at which the laser light is emitted and information indicating the timing at which the reflected light is received. Alternatively, the LiDAR information includes information indicating the time difference between the timing at which the laser light is emitted and the timing at which the reflected light is received. The distance calculation unit 31 uses these pieces of information to calculate the one-way propagation distance corresponding to the round-trip propagation time of the light, thereby calculating the distance D.

[0024] When the FMCW method is used, each LiDAR device 1 emits a chirp-shaped laser light by performing frequency modulation on the emitted laser light. Also, each LiDAR device 1 generates a beat signal by performing coherent detection on the received reflected light. The LiDAR information includes information indicating frequency components included in the generated beat signal. The distance calculation unit 31 uses this information to calculate the distance D based on a predetermined formula related to FMCW.

[0025] In addition, various known techniques can be used to calculate the distance D using LiDAR information. Details of these techniques will not be described here.

[0026] The three-dimensional model generation unit 32 generates a three-dimensional model M of the water surface and the object O in the target area A. The three-dimensional model M is generated using other predetermined information included in the LiDAR information and the distance D calculated by the distance calculation unit 31.

[0027] That is, the LiDAR information further includes information indicating the position of each LiDAR device 1 and information indicating the direction in which the laser light is emitted by each LiDAR device 1. The three-dimensional model generation unit 32 uses these pieces of information and the calculated distance D to calculate the position P of the point where the laser light emitted in each direction by each LiDAR device 1 is reflected by the water surface or the object O. The three-dimensional model generation unit 32 plots points corresponding to each position P in a virtual three-dimensional space corresponding to the target area A. As a result, a three-dimensional point cloud model corresponding to the position and shape of the water surface in at least a part of the target area A (more specifically, an area within a predetermined distance from any LiDAR device 1) and the position and shape of each object O in the target area A is generated. The three-dimensional model generation unit 32 uses the generated three-dimensional point cloud model for the three-dimensional model M. That is, the three-dimensional model M is composed of a point cloud.

[0028] Here, the LiDAR information further includes information indicating the luminance of reflected light corresponding to the laser light emitted in each direction by each LiDAR device 1. In other words, the LiDAR information includes information indicating the luminance of reflected light corresponding to each point in the three-dimensional model M. The three-dimensional model generation unit 32 compares the luminance with a predetermined threshold value to determine whether each point in the three-dimensional model M corresponds to the water surface or the object O. The three-dimensional model generation unit 32 separates the three-dimensional model M into a three-dimensional model M_1 corresponding to the water surface and a three-dimensional model M_2 corresponding to each object O by grouping a plurality of points included in the point cloud based on the result of such determination. In other words, the three-dimensional model generation unit 32 generates a three-dimensional model M including a three-dimensional model M_1 corresponding to the water surface and a three-dimensional model M_2 corresponding to each object O.

[0029] Usually, the laser light emitted by each LiDAR device 1 is obliquely incident on the water surface in the target area A. At this time, specular reflection occurs, and the brightness of the backscattered light is reduced. Therefore, the brightness of the reflected light corresponding to the water surface tends to be smaller than the brightness of the reflected light corresponding to the object O. Therefore, by comparing such brightness with a threshold value, it is possible to separate the three-dimensional models M_1 and M_2 as described above.

[0030] In addition, various known techniques can be used to generate the three-dimensional model M using the LiDAR information and the distance D. Detailed explanations of these techniques will be omitted.

[0031] The velocity vector calculation unit 33 calculates a velocity vector (hereinafter sometimes referred to as a “first velocity vector”) Vs indicating the movement of ocean waves W in the target area A, and a velocity vector (hereinafter sometimes referred to as a “second velocity vector”) Vt indicating the movement of each object O in the target area A. Other predetermined information included in the LiDAR information and the three-dimensional model M generated by the three-dimensional model generation unit 32 are used to calculate the velocity vectors Vs and Vt.

[0032] That is, the LiDAR information further includes information indicating frequency components contained in the laser light emitted in each direction by each LiDAR device 1, and information indicating frequency components contained in the corresponding reflected light. The velocity vector calculation unit 33 uses these pieces of information to calculate the Doppler shift amount in the reflected light corresponding to the laser light emitted in each direction by each LiDAR device 1. Various known techniques related to Doppler LiDAR can be used to calculate the Doppler shift amount.

[0033] As described above, the LiDAR information includes information indicating the direction in which the laser light is emitted by each LiDAR device 1. In other words, the LiDAR information includes information indicating the so-called "line of sight direction" of the laser light corresponding to each point included in the three-dimensional model M. The velocity vector calculation unit 33 uses such information and the calculated Doppler shift amount to calculate a vector V indicating the moving speed of each point included in the three-dimensional model M with respect to the corresponding line of sight direction.

[0034] Using the calculated vector V, the velocity vector calculation unit 33 calculates a vector Vs indicating the moving speed on a virtual plane (hereinafter referred to as the "XY plane") corresponding to the horizontal plane in the target area A for the point group constituting the three-dimensional model M_1 corresponding to the water surface. Specifically, for example, the velocity vector calculation unit 33 projects each of a plurality of vectors V corresponding to a plurality of points included in the three-dimensional model M_1 onto the XY plane. The velocity vector calculation unit 33 calculates the vector Vs by calculating the average of the projected vectors. In this manner, the velocity vector Vs is calculated.

[0035] Furthermore, the velocity vector calculation unit 33 uses the calculated vector V to calculate a vector Vt indicating a moving speed in the XY plane for a group of points constituting the three-dimensional model M_2 corresponding to each object O. Specifically, for example, the velocity vector calculation unit 33 projects each of a plurality of vectors V corresponding to a plurality of points included in each three-dimensional model M_2 onto the XY plane. The velocity vector calculation unit 33 calculates the average of the projected vectors to calculate the vector Vt. In this manner, the velocity vector Vt is calculated.

[0036] Here, each of the vectors Vt and Vs on the XY plane is a two-dimensional vector. In order to calculate such a two-dimensional vector, at least two LiDAR devices 1 installed on land or a ship, or one LiDAR device 1 installed on an aircraft, are used. That is, in this case, the underwater vehicle detection system 100 includes at least two LiDAR devices 1 installed on land or a ship, or one LiDAR device 1 installed on an aircraft.

[0037] On the other hand, the velocity vector calculation unit 33 may calculate velocity vectors Vs, Vt in a virtual space (hereinafter referred to as "XYZ space") corresponding to the target area A. In this case, each of the vectors Vt, Vs in the XYZ space is a three-dimensional vector. In order to calculate such a three-dimensional vector, at least three LiDAR devices 1 are used. That is, in this case, the marine vehicle detection system 100 includes at least three LiDAR devices 1.

[0038] The following mainly describes an example in which the velocity vector calculation unit 33 calculates the velocity vectors Vs, Vt in the XY plane.

[0039] The vessel detection unit 22 detects vessels in the target area A by determining whether or not each object O in the target area A is a vessel. For such determination, the velocity vectors Vs, Vt calculated by the velocity vector calculation unit 33 are used. A specific example of a method for detecting a vessel by the vessel detection unit 22 will be described later with reference to Figs. 9 to 11.

[0040] When a vessel is detected by the vessel detection unit 22, the suspicious vessel detection unit 23 determines whether or not the detected vessel is a suspicious vessel.

[0041] That is, the suspicious ship detection unit 23 acquires information indicating the position of the detected vessel. Specifically, for example, the suspicious ship detection unit 23 converts the position of the corresponding three-dimensional model M_2 in the virtual three-dimensional space into latitude and longitude using a predetermined conversion table. This allows the information indicating the position of the detected vessel to be acquired.

[0042] Furthermore, the suspicious ship detection unit 23 acquires information indicating the movement of the detected vessel. Specifically, for example, the suspicious ship detection unit 23 acquires information indicating the corresponding velocity vector Vt. This allows the information indicating the movement of the detected vessel to be acquired.

[0043] The suspicious ship detection unit 23 also acquires AIS (Automatic Identification System) information for the sea area corresponding to the target area A. The AIS information is received, for example, by an AIS receiver (not shown). The acquired AIS information includes information indicating the position (latitude, longitude, etc.) of each pre-registered ship. The acquired AIS information also includes information indicating the movement (course relative to the ground, ship speed relative to the ground, bow direction, turning angular rate, etc.) of each pre-registered ship.

[0044] The suspicious ship detection unit 23 uses this information to compare the position and movement of the detected vessel with the positions and movements of individual ships included in the AIS information. If the position and movement of the detected vessel corresponds to the position and movement of any ship included in the AIS information, the suspicious ship detection unit 23 determines that the detected vessel is not a suspicious vessel. If not, the suspicious ship detection unit 23 determines that the detected vessel is a suspicious vessel.

[0045] When a suspicious ship is detected by the suspicious ship detection unit 23, the notification control unit 24 executes control to notify the presence of the suspicious ship. For such notification, an output device 3 is used. The output device 3 includes, for example, at least one of a display device, an audio output device, and a communication device. The display device is, for example, one that uses a display. The audio output device is, for example, one that uses a speaker. The communication device is, for example, one that uses a dedicated transmitter and receiver.

[0046] Specifically, for example, the notification control unit 24 executes control to display an image indicating the presence of a suspicious ship. A display device of the output device 3 is used to display such an image. The presence of the suspicious ship is notified to a person by displaying such an image. Note that such an image may indicate the position of the suspicious ship in the target area A. For example, such an image may be a map-like or nautical chart-like image including the target area A, with a dot-like or icon-like image indicating the position of the suspicious ship superimposed thereon. Alternatively, for example, such an image may be a three-dimensional model M_2 corresponding to the suspicious ship displayed in a color different from the colors of other parts of the three-dimensional model M.

[0047] Alternatively, for example, the notification control unit 24 executes control to output a sound indicating the presence of a suspicious ship. For outputting such a sound, an audio output device of the output device 3 is used. By outputting such a sound, the presence of the suspicious ship is notified to a person.

[0048] Alternatively, for example, the notification control unit 24 executes control to transmit a signal indicating the presence of a suspicious ship. A communication device in the output device 3 is used to transmit such a signal. By transmitting such a signal, the presence of the suspicious ship is notified to another system (not shown). Notification Such a signal is transmitted, for example, to a system monitoring an area of ​​the ocean corresponding to the area of ​​interest A.

[0049] The main components of the marine vehicle detection system 100 are configured in this manner.

[0050] Hereinafter, the emission unit 11 may be referred to as "emission means". Furthermore, the light receiving unit 12 may be referred to as "light receiving means". Furthermore, the motion detection unit 21 may be referred to as "motion detection means". Furthermore, the marine vessel detection unit 22 may be referred to as "marine vessel detection means". Furthermore, the suspicious vessel detection unit 23 may be referred to as "suspicious vessel detection means". Furthermore, the notification control unit 24 may be referred to as "notification control means".

[0051] Next, the hardware configuration of the main parts of the marine vessel detection device 2 will be described with reference to Figs.

[0052] As shown in each of FIGS. 5 to 7, the marine vehicle detection device 2 uses a computer 41.

[0053] 5, the computer 41 includes a processor 51 and a memory 52. ​​The memory 52 stores programs for causing the computer 41 to function as the motion detection unit 21, the navigational body detection unit 22, the suspicious ship detection unit 23, and the notification control unit 24. The processor 51 reads out and executes the programs stored in the memory 52. ​​This realizes a function F1 of the motion detection unit 21, a function F2 of the navigational body detection unit 22, a function F3 of the suspicious ship detection unit 23, and a function F4 of the notification control unit 24.

[0054] 6, the computer 41 includes a processing circuit 53. The processing circuit 53 executes processes for causing the computer 41 to function as the motion detection unit 21, the navigational object detection unit 22, the suspicious ship detection unit 23, and the notification control unit 24. This realizes functions F1 to F4.

[0055] 7, the computer 41 includes a processor 51, a memory 52, and a processing circuit 53. In this case, some of the functions F1 to F4 are realized by the processor 51 and the memory 52, and the remaining functions of the functions F1 to F4 are realized by the processing circuit 53.

[0056] The processor 51 is configured with one or more processors. Each processor may be, for example, a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor, a microcontroller, or a digital signal processor (DSP).

[0057] The memory 52 is composed of one or more memories, each of which may be, for example, a random access memory (RAM), a read only memory (ROM), a flash memory, an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a solid state drive, a hard disk drive, a flexible disk, a compact disk, a digital versatile disk (DVD), a Blu-ray disk, a magneto optical (MO) disk, or a mini disk.

[0058] The processing circuit 53 is composed of one or more processing circuits. Each processing circuit uses, for example, an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), an FPGA (Field Programmable Gate Array), an SoC (System on a Chip), or a system LSI (Large Scale Integration).

[0059] The processor 51 may include a dedicated processor corresponding to each of the functions F1 to F4. The memory 52 may include a dedicated memory corresponding to each of the functions F1 to F4. The processing circuit 53 may include a dedicated processing circuit corresponding to each of the functions F1 to F4.

[0060] Next, the operation of the marine vessel detection device 2 will be described with reference to the flowchart shown in FIG.

[0061] First, the motion detection unit 21 detects the motion of ocean waves W in the target area A, and also detects the motion of each object O in the target area A (step ST1). The details of the motion detection method by the motion detection unit 21 have already been described, and therefore will not be described again.

[0062] Next, the vessel detection unit 22 detects vessels in the target area A by determining whether or not each object O is a vessel (step ST2). A method for detecting vessels by the vessel detection unit 22 will be described in detail below with reference to Figs. 9 to 11.

[0063] Next, when a vessel is detected in step ST2, the suspicious vessel detection unit 23 detects a suspicious vessel in the target area A by determining whether the detected vessel is a suspicious vessel or not (step ST3). The details of the method for detecting a suspicious vessel by the suspicious vessel detection unit 23 have already been described, and therefore will not be described again.

[0064] Next, when a suspicious ship is detected in step ST3, the notification control unit 24 executes control to notify the presence of the suspicious ship (step ST4). The details of such notification have already been described, and therefore will not be described again.

[0065] If no vessel is detected in step ST2, steps ST3 and ST4 are skipped. If no suspicious vessel is detected in step ST3, step ST4 is skipped.

[0066] Next, a method for detecting a marine vessel by the marine vessel detection unit 22 will be described in detail with reference to Figs.

[0067] FIG. 9 shows an example of a state in which laser light is irradiated onto the water surface in the target area A and the object O when one object O is present in the target area A. In the example shown in FIG. 9, the object O is a navigation body (more specifically, a ship). FIG. 10 shows examples of velocity vectors Vs, Vt calculated by the velocity vector calculation unit 33 in the state shown in FIG. 9. Each of the velocity vectors Vs, Vt is a two-dimensional vector in the XY plane. The velocity vector Vs corresponds to the movement of the waves W. The velocity vector Vt corresponds to the movement of the object O.

[0068] The marine vessel detection unit 22 calculates a parallel component Vtp of the velocity vector Vt relative to the velocity vector Vs. The marine vessel detection unit 22 also calculates a perpendicular component Vtv of the velocity vector Vt relative to the velocity vector Vs. In other words, the marine vessel detection unit 22 separates the velocity vector Vt into a parallel component Vtp and a perpendicular component Vtv relative to the velocity vector Vs. Fig. 11 shows an example of the separated parallel component Vtp and vertical component Vtv.

[0069] At this time, the marine vessel detection unit 22 sets the X-axis in the XY plane to an axis parallel to the velocity vector Vs. Therefore, the parallel component Vtp is the X-component Vtx of the velocity vector Vt. Also, the vertical component Vtv is the Y-component Vty of the velocity vector Vt.

[0070] <First Discrimination Method> The marine vessel detection unit 22 calculates a relative velocity vector Vrp indicating the difference between the parallel component Vtp and the velocity vector Vs, using the following equation (1).

[0071] Vrp = Vtp - Vs (1)

[0072] Next, the marine vessel detection unit 22 compares the magnitude |Vrp| of the relative velocity vector Vrp with a predetermined threshold value Th1. The marine vessel detection unit 22 determines that the object O is a marine vessel when the condition shown in the following equation (2) (hereinafter referred to as the "first condition") is satisfied. On the other hand, when the first condition is not satisfied, the marine vessel detection unit 22 determines that the object O is not a marine vessel.

[0073] |Vrp|>Th1 (2)

[0074] That is, the magnitude |Vrp| of the relative velocity vector Vrp corresponds to the amount of deviation in the movement of the object O relative to the movement of the waves W in the X direction. If the amount of deviation is large, there is a high probability that the object O is moving against the waves in the target area A. In this case, it is considered that there is a high probability that the object O is a powered moving body, i.e., a navigation body. On the other hand, if the amount of deviation is small, it is considered that there is a high probability that the object O is an object being carried by the waves in the target area A, i.e., a floating object. Therefore, the navigation body detection unit 22 determines whether the object O is a navigation body by threshold judgment using |Vrp| as described above.

[0075] <Second method of distinction> The watercraft detection unit 22 compares the magnitude |Vtv| of the vertical component Vtv with a predetermined threshold value Th2. The watercraft detection unit 22 determines that the object O is a watercraft when the condition shown in the following formula (3) (hereinafter referred to as the "second condition") is satisfied. On the other hand, when the second condition is not satisfied, the watercraft detection unit 22 determines that the object O is not a watercraft.

[0076] |Vtv|>Th2 (3)

[0077] That is, the magnitude |Vtv| of the vertical component Vtv corresponds to the amount of deviation in the motion pattern of the object O relative to the motion of the waves W in the Y direction. If the amount of deviation is large, the object O is likely to be a powered moving body, i.e., a navigation body. On the other hand, if the amount of deviation is small, the object O is likely to be an object being swept away by the waves in the target area A, i.e., a floating object. Therefore, the navigation body detection unit 22 determines whether the object O is a navigation body by threshold judgment using |Vtv| as described above.

[0078] <Third method of distinction> The marine vessel detection unit 22 calculates the relative velocity vector Vrp by the above formula (1).

[0079] Next, the marine vessel detection unit 22 compares the magnitude |Vrp| of the relative velocity vector Vrp with a threshold value Th1, and compares the magnitude |Vtv| of the vertical component Vtv with a threshold value Th2. If at least one of the first condition and the second condition is satisfied, the marine vessel detection unit 22 determines that the object O is a marine vessel. On the other hand, if the first condition is not satisfied and the second condition is not satisfied, the marine vessel detection unit 22 determines that the object O is not a marine vessel.

[0080] In this way, by using both the relative velocity vector Vrp and the vertical component Vtv, it is possible to improve the accuracy of determining whether or not the object O is an underwater vehicle. In particular, when the object O is an underwater vehicle, it is possible to suppress the occurrence of erroneous determination that the object O is not an underwater vehicle.

[0081] <The fourth method of distinction> The marine vessel detection unit 22 calculates the relative velocity vector Vrp by the above formula (1).

[0082] Next, the marine vessel detection unit 22 calculates an integrated value ∫(|Vrp|)(dt) for a predetermined time period for the magnitude |Vrp| of the relative velocity vector Vrp. The marine vessel detection unit 22 compares the integrated value ∫(|Vrp|)(dt) with a predetermined threshold value Th3. The marine vessel detection unit 22 determines that the object O is a marine vessel if the condition shown in the following equation (4) (hereinafter referred to as the "third condition") is met. On the other hand, if the third condition is not met, the marine vessel detection unit 22 determines that the object O is not a marine vessel.

[0083] ∫(|Vrp|)(dt)>Th3 (4)

[0084] In this way, by using the integrated value ∫(|Vrp|)(dt) for a predetermined period of time, it is possible to reduce the occurrence of erroneous determination due to fluctuations in |Vrp| over time, compared to using |Vrp| at a specific point in time.

[0085] <Fifth method of distinction> The marine vessel detection unit 22 calculates an integrated value ∫(|Vtv|)(dt) for a predetermined time period for the magnitude |Vtv| of the vertical component Vtv. The marine vessel detection unit 22 compares the integrated value ∫(|Vtv|)(dt) with a predetermined threshold value Th4. The marine vessel detection unit 22 determines that the object O is a marine vessel when the condition shown in the following equation (5) (hereinafter referred to as the "fourth condition") is met. On the other hand, when the fourth condition is not met, the marine vessel detection unit 22 determines that the object O is not a marine vessel.

[0086] ∫(|Vtv|)(dt)>Th4 (5)

[0087] In this way, by using the integrated value ∫(|Vtv|)(dt) for a predetermined period of time, it is possible to reduce the occurrence of erroneous determination due to fluctuations in |Vtv| over time, compared to using |Vtv| at a specific point in time.

[0088] <Sixth Discrimination Method> The marine vessel detection unit 22 calculates the relative velocity vector Vrp by the above formula (1).

[0089] Next, the marine vessel detection unit 22 calculates an integrated value ∫(|Vrp|)(dt) of the magnitude |Vrp| of the relative velocity vector Vrp over a predetermined time period. The marine vessel detection unit 22 also calculates an integrated value ∫(|Vtv|)(dt) of the magnitude |Vtv| of the vertical component Vtv over a predetermined time period.

[0090] The watercraft detection unit 22 compares the integrated value ∫(|Vrp|)(dt) with a threshold value Th3, and compares the integrated value ∫(|Vtv|)(dt) with a threshold value Th4. If at least one of the third condition and the fourth condition is met, the watercraft detection unit 22 determines that the object O is a watercraft. On the other hand, if the third condition is not met and the fourth condition is not met, the watercraft detection unit 22 determines that the object O is not a watercraft.

[0091] In this way, by using both the relative velocity vector Vrp and the vertical component Vtv, it is possible to improve the accuracy of determining whether or not the object O is a navigation vehicle. Furthermore, by using the integrated value ∫(|Vrp|)(dt) for a predetermined time period, it is possible to reduce the occurrence of erroneous determination due to time fluctuations in |Vrp| compared to using |Vrp| at a specific time point. Furthermore, by using the integrated value ∫(|Vtv|)(dt) for a predetermined time period, it is possible to reduce the occurrence of erroneous determination due to time fluctuations in |Vtv| compared to using |Vtv| at a specific time point.

[0092] Next, a modification of the marine vehicle detection system 100 will be described.

[0093] The method of detecting a suspicious ship by the suspicious ship detection unit 23 is not limited to the above specific example (i.e., the example using AIS information). For example, the suspicious ship detection unit 23 may use the following method when determining whether the vessel detected by the vessel detection unit 22 is a suspicious ship.

[0094] That is, the suspicious ship detection unit 23 prestores information indicating one or more patterns of positions and movements of suspicious ships previously detected in the sea area corresponding to the target area A. The suspicious ship detection unit 23 compares the position and movement of the vessel detected by the vessel detection unit 22 with each pattern. In other words, the suspicious ship detection unit 23 compares the position and movement of the vessel detected by the vessel detection unit 22 with a predetermined pattern set in advance. If the position and movement of the vessel detected by the vessel detection unit 22 corresponds to any of the patterns, the suspicious ship detection unit 23 determines that the detected vessel is a suspicious ship. If not, the suspicious ship detection unit 23 determines that the detected vessel is not a suspicious ship.

[0095] Next, another modification of the marine vehicle detection system 100 will be described.

[0096] Each LiDAR device 1 may be installed underwater (e.g., under the sea) around the target area A or underwater (e.g., under the sea) inside the target area A. That is, each LiDAR device 1 may use an underwater LiDAR. In this case, a laser beam is emitted from an emission unit 11 provided underwater, and a reflected light is received by a light receiving unit 12 provided underwater. At this time, the frequency of the emitted laser beam is preferably set to a frequency for underwater LiDAR.

[0097] Next, the effects of using the marine vessel detection system 100 will be described.

[0098] As described above, in the navigational object detection device 2, the motion detection unit 21 detects the motion of the object O on the water and the motion of the waves W on the water surface based on the laser light irradiated onto the object O on the water and the water surface around the object O, and the reflected light corresponding to the laser light. The navigational object detection unit 22 detects the navigational object by determining whether the object O is a navigational object based on the motion of the object O and the motion of the waves W. This makes it possible to detect the navigational object in the target area A.

[0099] In particular, by using the LiDAR device 1, it is possible to detect a naval object regardless of the brightness of the surroundings, compared to the case where a visible light camera is used. In addition, the distance at which an object O can be detected using the LiDAR device 1 is usually longer than the distance at which the object O can be detected using a visible light camera. Therefore, particularly when the target area A is wide, it is possible to reduce the number of such devices to be installed, compared to the case where a visible light camera is used. In addition, by using the LiDAR device 1, it is possible to reduce personnel costs, compared to the case where manned ships patrol to detect naval objects (particularly suspicious ships).

[0100] Furthermore, the motion detection unit 21 detects the motion of the object O and the motion of the ocean waves W based on the amount of Doppler shift of the reflected light. This makes it possible to detect the motion of the object O and the motion of the ocean waves W using technology related to Doppler LiDAR.

[0101] Furthermore, the navigation body detection unit 22 uses a first velocity vector Vs indicating the motion of the waves W and a second velocity vector Vt indicating the motion of the object O to determine whether or not the object O is a navigation body based on the amount of deviation of the motion of the object O from the motion of the waves W. By using the velocity vectors Vs, Vt, it is possible to determine whether or not the object O is a navigation body based on the method described with reference to Figures 9 to 11, for example.

[0102] Furthermore, when the object O is determined to be a watercraft, the suspicious ship detection unit 23 detects the suspicious ship by determining whether the watercraft is a suspicious ship or not. This makes it possible to detect the suspicious ship in the target area A.

[0103] In addition, the suspicious ship detection unit 23 acquires AIS information and compares the position and movement of the vessel with the positions and movements of individual ships included in the AIS information to determine whether the vessel is a suspicious ship. By using the AIS information, it is possible to determine whether the vessel is a suspicious ship, as described above.

[0104] The suspicious ship detection unit 23 also compares the movement of the vessel with a preset movement pattern to determine whether the vessel is a suspicious ship. By using such a pattern, it is possible to determine whether the vessel is a suspicious ship, as described above. In particular, it is possible to determine whether the vessel is a suspicious ship even when AIS information cannot be obtained.

[0105] Furthermore, when the navigation vehicle is determined to be a suspicious ship, the notification control unit 24 executes control to notify the presence of the suspicious ship, thereby making it possible to notify a person or other system of the presence of the suspicious ship in the target area A.

[0106] Moreover, the laser light is emitted by an emission unit 11 provided underwater, and the reflected light is received by a light receiving unit 12 provided underwater. This makes it possible to use underwater LiDAR for detecting the navigation body.

[0107] Next, a modified example of the marine vessel detection device 2 will be described with reference to Fig. 12. Also, another modified example of the marine vessel detection system 100 will be described with reference to Fig. 13.

[0108] 12, the marine vessel detection device 2 may include a motion detection unit 21 and a marine vessel detection unit 22. In other words, the main parts of the marine vessel detection device 2 may be configured by the motion detection unit 21 and the marine vessel detection unit 22. In this case, the suspicious vessel detection unit 23 and the notification control unit 24 may be provided outside the marine vessel detection device 2. In other words, a specific example of the marine vessel detection device 2 shown in FIG. 12 is the marine vessel detection device 2 shown in FIG. 3.

[0109] As shown in Fig. 13, the underwater body detection system 100 may include a motion detection unit 21 and a underwater body detection unit 22. In other words, the motion detection unit 21 and the underwater body detection unit 22 may constitute the main parts of the underwater body detection system 100. In this case, the suspicious ship detection unit 23 and the notification control unit 24 may be provided outside the underwater body detection system 100. In addition, the LiDAR devices 1_1 to 1_N and the output device 3 may be provided outside the underwater body detection system 100. In other words, a specific example of the underwater body detection system 100 shown in Fig. 13 is the underwater body detection system 100 shown in Fig. 1.

[0110] Even in these cases, the above-mentioned effects can be achieved. That is, the motion detection unit 21 detects the motion of the object O and the motion of the waves W on the water surface based on the laser light irradiated on the object O on the water and the water surface around the object O, and the reflected light corresponding to the laser light. The navigation body detection unit 22 detects the navigation body by determining whether the object O is a navigation body based on the motion of the object O and the motion of the waves W. This makes it possible to detect the navigation body.

[0111] The marine vessel detection system 100 may include a suspicious vessel detection unit 23 in addition to the motion detection unit 21 and the marine vessel detection unit 22. The marine vessel detection system 100 may further include a notification control unit 24. Each unit of the marine vessel detection system 100 may be configured as an independent device. These devices may be distributed geographically or over a network. For example, these devices may include an edge computer and a cloud computer.

[0112] [Second embodiment] Fig. 14 is a block diagram showing the main parts of a ship-based object detection system according to a second embodiment. Fig. 15 is a block diagram showing the main parts of a ship-based object detection device according to a second embodiment. Fig. 16 is a block diagram showing the main parts of a motion detection unit in the ship-based object detection device according to a second embodiment. The ship-based object detection system according to the second embodiment will be described with reference to Figs. 14 to 16. In Figs. 14 to 16, blocks similar to those shown in Figs. 1, 3 and 4 are designated by the same reference numerals and description thereof will be omitted.

[0113] As shown in Fig. 14, the marine vessel detection system 100a includes LiDAR devices 1_1 to 1_N, a marine vessel detection device 2a, and an output device 3. As shown in Fig. 15, the marine vessel detection device 2a includes a motion detection unit 21a, a marine vessel detection unit 22, a suspicious vessel detection unit 23, and a notification control unit 24. As shown in Fig. 16, the motion detection unit 21a includes a distance calculation unit 31, a three-dimensional model generation unit 32, and a velocity vector calculation unit 33a. Hereinafter, the motion detection unit 21a may be referred to as "motion detection means."

[0114] The velocity vector calculation unit 33 in the marine vessel detection device 2 according to the first embodiment calculates the velocity vectors Vt, Vs based on the amount of Doppler shift in the reflected light received by each LiDAR device 1. In contrast to this, the velocity vector calculation unit 33a calculates the velocity vectors Vt, Vs based on a time change in the three-dimensional model M.

[0115] That is, the target area A is scanned by each LiDAR device 1 at predetermined time intervals. As a result, a three-dimensional model M is generated at each predetermined time interval. In other words, a plurality of three-dimensional models M corresponding to a plurality of consecutive time points are generated. The three-dimensional models M corresponding to each time point may include a three-dimensional model M_1 corresponding to the water surface, and may also include a three-dimensional model M_2 corresponding to each object O.

[0116] The velocity vector calculation unit 33a detects the positions of the parts of the three-dimensional model M_1 corresponding to each time point that correspond to each wave of the waves W (or the parts corresponding to at least one selected wave of the waves W). The velocity vector calculation unit 33a calculates a velocity vector Vs indicating the movement of the waves W based on the time change of the detected positions. Note that, when the time change of the detected positions differs for each wave, the velocity vector Vs may be calculated based on the average of these changes.

[0117] Furthermore, for the three-dimensional model M corresponding to each time, the velocity vector calculation unit 33a detects the position of the three-dimensional model M_2 corresponding to each object O. The velocity vector calculation unit 33a calculates a velocity vector Vt indicating the movement of each object O based on the change over time of the detected position.

[0118] In this manner, the movement of the waves W in the target area A is detected, and the movement of each object O in the target area A is detected.

[0119] The hardware configuration of the main parts of the marine vessel detection device 2a is similar to that described with reference to Figures 5 to 7 in the first embodiment. Therefore, a detailed description will be omitted. That is, the marine vessel detection device 2a has a function F1a of the motion detection unit 21a, a function F2 of the marine vessel detection unit 22, a function F3 of the suspicious vessel detection unit 23, and a function F4 of the notification control unit 24. Each of the functions F1a, F2, F3, and F4 may be realized by the processor 51 and the memory 52, or may be realized by the processing circuit 53.

[0120] Next, the operation of the marine vessel detection device 2a will be described with reference to the flow chart shown in Fig. 17. In Fig. 17, steps similar to those shown in Fig. 8 are given the same reference numerals and descriptions thereof will be omitted.

[0121] First, the motion detection unit 21a detects the motion of ocean waves W in the target area A, and also detects the motion of each object O in the target area A (step ST1a). The details of the motion detection method by the motion detection unit 21a have already been described. Therefore, a repeated description will be omitted. Next, the processes of steps ST2 to ST4 are executed in sequence.

[0122] Next, the effects of using the marine vehicle detection system 100a will be described.

[0123] The ship detection system 100a provides the same effects as those provided by the ship detection system 100 according to the first embodiment. That is, by using the ship detection system 100a, it is possible to detect a ship in the target area A. In addition, it is possible to detect a suspicious ship in the target area A by determining whether the detected ship is a suspicious ship or not.

[0124] Next, a modified example of the marine vessel detection device 2a will be described, along with a modified example of the marine vessel detection system 100a.

[0125] The marine vessel detection device 2a may employ various modified examples similar to those described in the first embodiment. For example, the main part of the marine vessel detection device 2a may be configured by the motion detection unit 21a and the marine vessel detection unit 22, as in the example described with reference to FIG.

[0126] The marine vessel detection system 100a may employ various modified examples similar to those described in the first embodiment. For example, as in the example described with reference to FIG. 13, the main parts of the marine vessel detection system 100a may be configured with a motion detection unit 21a and a marine vessel detection unit 22. In addition, the marine vessel detection system 100a may include a suspicious vessel detection unit 23. The marine vessel detection system 100a may further include a notification control unit 24.

[0127] Although the present invention has been described above with reference to the embodiment, the present invention is not limited to the above embodiment. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

[0128] A part or all of the above-described embodiments can be described as, but is not limited to, the following supplementary notes.

[0129] [Note] [Appendix 1] a motion detection means for detecting a motion of an object on the water and a motion of waves on the water surface based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; a marine vehicle detection means for detecting the marine vehicle by determining whether the object is a marine vehicle based on the motion of the object and the motion of the waves; A marine vehicle detection device comprising: [Appendix 2] The underwater vehicle detection device according to claim 1, wherein the motion detection means detects the motion of the object and the motion of the waves based on the amount of Doppler shift of the reflected light. [Appendix 3] The navigational object detection device described in Appendix 1, characterized in that the motion detection means generates a three-dimensional model of the object and the water surface based on the reflected light, and detects the motion of the object and the motion of the waves based on changes in the three-dimensional model over time. [Appendix 4] The marine vessel detection device according to any one of Supplementary Note 1 to Supplementary Note 3, characterized in that the marine vessel detection means uses a first velocity vector indicating the movement of the waves and a second velocity vector indicating the movement of the object to determine whether or not the object is the marine vessel based on the deviation of the movement of the object from the movement of the waves. [Appendix 5] A marine vessel detection device as described in any one of Appendix 1 to Appendix 4, characterized in that if the object is determined to be the marine vessel, it is provided with a suspicious vessel detection means for detecting the suspicious vessel by determining whether the marine vessel is a suspicious vessel or not. [Appendix 6] The suspicious ship detection means of the marine vessel detection device described in Appendix 5 is characterized in that it acquires AIS information and determines whether the marine vessel is a suspicious ship by comparing the position and movement of the marine vessel with the positions and movements of individual ships contained in the AIS information. [Appendix 7] The suspicious ship detection device described in Appendix 5, characterized in that the suspicious ship detection means determines whether the ship is a suspicious ship by comparing the movement of the ship with a predetermined movement pattern. [Appendix 8] A marine vehicle detection device as described in any one of Appendices 5 to 7, characterized in that if the marine vehicle is determined to be a suspicious ship, the presence of the suspicious ship is reported. [Appendix 9] The laser light is emitted by an emission means provided underwater, The reflected light is received by a light receiving means provided underwater. 9. The marine vehicle detection device according to claim 1, [Appendix 10] a motion detection means for detecting a motion of an object on the water and a motion of waves on the water surface based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; a marine vehicle detection means for detecting the marine vehicle by determining whether the object is a marine vehicle based on the motion of the object and the motion of the waves; A marine vehicle detection system comprising: [Appendix 11] 11. The underwater vehicle detection system according to claim 10, wherein the motion detection means detects the motion of the object and the motion of the waves based on the amount of Doppler shift of the reflected light. [Appendix 12] The underwater vehicle detection system described in Appendix 10, characterized in that the motion detection means generates a three-dimensional model of the object and the water surface based on the reflected light, and detects the motion of the object and the motion of the waves based on changes in the three-dimensional model over time. [Appendix 13] The marine vessel detection system according to any one of claims 10 to 12, characterized in that the marine vessel detection means uses a first velocity vector indicating the movement of the waves and a second velocity vector indicating the movement of the object to determine whether or not the object is the marine vessel based on an amount of deviation of the movement of the object from the movement of the waves. [Appendix 14] A sea vehicle detection system as described in any one of Appendices 10 to 13, characterized in that if the object is determined to be the sea vehicle, it is further provided with a suspicious ship detection means for detecting the suspicious ship by determining whether the sea vehicle is a suspicious ship or not. [Appendix 15] The suspicious ship detection system described in Appendix 14, characterized in that the suspicious ship detection means acquires AIS information and determines whether the ship is a suspicious ship by comparing the position and movement of the ship with the positions and movements of individual ships contained in the AIS information. [Appendix 16] The suspicious ship detection system described in Appendix 14, characterized in that the suspicious ship detection means determines whether the ship is a suspicious ship by comparing the movement of the ship with a predetermined movement pattern. [Appendix 17] A marine vehicle detection system as described in any one of appendices 14 to 16, characterized in that if the marine vehicle is determined to be a suspicious ship, the presence of the suspicious ship is reported. [Appendix 18] The laser light is emitted by an emission means provided underwater, The reflected light is received by a light receiving means provided underwater. 18. The marine vehicle detection system according to claim 10, [Appendix 19] a motion detection means for detecting a motion of an object on the water and a motion of waves on the water surface based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; A watercraft detection means detects the watercraft by determining whether the object is a watercraft based on the motion of the object and the motion of the waves. Vehicle detection method. [Appendix 20] 20. The method for detecting a marine object according to claim 19, wherein the motion detection means detects the motion of the object and the motion of the waves based on an amount of Doppler shift of the reflected light. [Appendix 21] The method for detecting a navigation object described in claim 19, characterized in that the motion detection means generates a three-dimensional model of the object and the water surface based on the reflected light, and detects the motion of the object and the motion of the waves based on changes in the three-dimensional model over time. [Appendix 22] The method for detecting a navigation object described in any one of Supplementary Note 19 to Supplementary Note 20, characterized in that the navigation object detection means uses a first velocity vector indicating the movement of the waves and a second velocity vector indicating the movement of the object to determine whether or not the object is the navigation object based on an amount of deviation of the movement of the object from the movement of the waves. [Appendix 23] A method for detecting a vessel described in any one of Appendices 19 to 22, characterized in that when the object is determined to be the vessel, the suspicious vessel detection means detects the suspicious vessel by determining whether the vessel is a suspicious vessel or not. [Appendix 24] The method for detecting a vessel described in Appendix 23, characterized in that the suspicious vessel detection means acquires AIS information and determines whether the vessel is a suspicious vessel by comparing the position and movement of the vessel with the positions and movements of individual ships contained in the AIS information. [Appendix 25] The method for detecting a vessel described in Appendix 23, characterized in that the suspicious vessel detection means determines whether the vessel is a suspicious vessel by comparing the movement of the vessel with a predetermined movement pattern. [Appendix 26] A method for detecting a ship described in any one of Appendices 23 to 25, characterized in that if the ship is determined to be a suspicious ship, the presence of the suspicious ship is reported. [Appendix 27] An emission means provided underwater emits the laser light, A light receiving means provided in the water receives the reflected light. 27. The method for detecting a marine vessel according to claim 19, [Appendix 28] Computer, a motion detection means for detecting a motion of an object on the water and a motion of waves on the water surface based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; a marine vehicle detection means for detecting the marine vehicle by determining whether the object is a marine vehicle based on the motion of the object and the motion of the waves; A recording medium on which a program for functioning as a [Appendix 29] 29. The recording medium according to claim 28, wherein the motion detection means detects the motion of the object and the motion of the waves based on the amount of Doppler shift of the reflected light. [Appendix 30] The recording medium described in Appendix 28, characterized in that the motion detection means generates a three-dimensional model of the object and the water surface based on the reflected light, and detects the motion of the object and the motion of the waves based on changes in the three-dimensional model over time. [Appendix 31] The recording medium described in any one of Appendices 28 to 30, characterized in that the navigation object detection means uses a first velocity vector indicating the movement of the waves and a second velocity vector indicating the movement of the object to determine whether the object is the navigation object based on the amount of deviation of the movement of the object from the movement of the waves. [Appendix 32] The recording medium described in any one of Appendices 28 to 31, characterized in that the program causes the computer to function as a suspicious ship detection means that, when the object is determined to be the vessel, detects the suspicious ship by determining whether the vessel is a suspicious ship or not. [Appendix 33] The recording medium described in Appendix 32, wherein the suspicious ship detection means acquires AIS information and determines whether the vessel is a suspicious ship by comparing the position and movement of the vessel with the positions and movements of individual ships contained in the AIS information. [Appendix 34] The recording medium described in Appendix 32, characterized in that the suspicious ship detection means determines whether the vessel is a suspicious ship by comparing the movement of the vessel with a predetermined movement pattern. [Appendix 35] The recording medium described in any one of Appendices 32 to 34, characterized in that the program causes the computer to function as an alarm control unit that executes control to alarm the presence of a suspicious ship when the navigation vehicle is determined to be the suspicious ship. [Explanation of symbols]

[0130] 1 LiDAR device 2,2a Vessel detection device 3 Output Device 11. Emission section 12 Light receiving part 21, 21a Motion detection section 22 Vehicle detection unit 23 Suspicious Ship Detection Unit 24 Notification control section 31 Distance calculation unit 32 3D model generation unit 33, 33a Velocity vector calculation section 41 Computer 51 Processors 52 Memory 53 Processing circuit 100,100a Vehicle Detection System

Claims

1. an image creation means for creating a three-dimensional point cloud image of an object on the water and the water surface around the object based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; a motion detection means for detecting a motion of the object and a motion of waves on the water surface based on the three-dimensional point cloud image; a marine vessel detection means for detecting the marine vessel by determining whether the object is a marine vessel based on the motion of the object and the motion of the waves; A marine vehicle detection device comprising:

2. 2. The underwater vehicle detection device according to claim 1, wherein the motion detection means detects the motion of the object and the motion of the waves based on an amount of Doppler shift of the reflected light.

3. The underwater vehicle detection device according to claim 1, characterized in that the motion detection means generates a three-dimensional model of the object and the water surface based on the reflected light, and detects the motion of the object and the motion of the waves based on changes over time in the three-dimensional model.

4. The underwater body detection device according to any one of claims 1 to 3, characterized in that the underwater body detection means uses a first velocity vector indicating the movement of the waves and a second velocity vector indicating the movement of the object to determine whether or not the object is the underwater body based on the amount of deviation of the movement of the object relative to the movement of the waves.

5. A seagoing object detection device as described in any one of claims 1 to 4, characterized in that if the object is determined to be the seagoing object, a suspicious ship detection means is provided to detect the suspicious ship by determining whether the seagoing object is a suspicious ship or not.

6. The navigational object detection device described in claim 5, characterized in that the suspicious ship detection means acquires AIS information and determines whether the navigational object is a suspicious ship by comparing the position and movement of the navigational object with the positions and movements of individual ships contained in the AIS information.

7. The marine vessel detection device according to claim 5, characterized in that the suspicious vessel detection means determines whether the marine vessel is a suspicious vessel by comparing the movement of the marine vessel with a preset movement pattern.

8. 8. The marine vessel detection device according to claim 5, wherein, when the marine vessel is determined to be the suspicious vessel, the presence of the suspicious vessel is notified.

9. an image creation means for creating a three-dimensional point cloud image of an object on the water and the water surface around the object based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light; a motion detection means for detecting a motion of the object and a motion of waves on the water surface based on the three-dimensional point cloud image; a marine vessel detection means for detecting the marine vessel by determining whether the object is a marine vessel based on the motion of the object and the motion of the waves; A marine vehicle detection system comprising:

10. An image creation means creates a three-dimensional point cloud image of an object on the water and the water surface around the object based on a laser light irradiated onto the object and the water surface around the object, and a reflected light corresponding to the laser light, a motion detection means for detecting a motion of the object and a motion of waves on the water surface based on the three-dimensional point cloud image; A watercraft detection means detects the watercraft by determining whether the object is a watercraft based on the motion of the object and the motion of the waves. Vehicle detection method.

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