Underwater object search support device, underwater object search support method, and underwater object search support program

Abstract

To provide an underwater object search assist device, underwater object search assist method, and underwater object search assist program that can improve a detection probability by selecting optimal oscillation specifications.SOLUTION: An underwater object search assist device of the present invention comprises: a transmitter; a receiver; a signal processing unit that performs signal processing of acoustic data; a detection processing unit that detects an echo sound, and estimates coordinates of an underwater object and a moving trajectory thereof; a forecasting unit that forecasts a detection probability; a storage unit that stores data on the detection probability; a speed / course estimation unit that estimates a speed and course of the underwater object; a transmission / reception-wave-location-specific Doppler shift estimation unit that estimates Doppler shifts specific to transmission / reception wave locations of the underwater object, respectively; an ML (Masking Level) estimation unit that determines which of a reverberation area or a noise area the echo sound belongs to, and estimates an ML; a TS (Target Strength) estimation unit that estimates a TS; an acquisition unit that acquires the data on the detection probability from the storage unit; an update unit that updates the data on the detection probability; and a selection unit that selects oscillation specifications on the basis of the updated data on the detection probability.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an underwater object search support device, an underwater object search support method, and an underwater object search support program. [Background technology]

[0002] When searching for underwater objects, a sonar device is used as a search support device for underwater objects. In order to search for underwater objects, it is necessary to determine the optimal sensor arrangement and oscillation parameters based on the conditions of the sea area, the characteristics of the oscillation pulse, the movements of the underwater objects, etc.

[0003] For example, Patent Document 1 discloses a technique for searching for underwater objects by calculating acoustic propagation and the probability of detecting underwater objects for each pulse and recommending an optimal oscillation mode. Patent Document 2 discloses a technique for a prediction method for grasping the optimal depth for oscillation. Patent Document 3 discloses a technique for a method for determining the placement of a transmitting and receiving device in a multistatic sonar system. Patent Document 4 discloses a technique for a method for determining the transmission schedule of oscillation sounds in a multistatic sonar system. Patent Document 5 discloses a technique for a method for predicting and calculating the detection distance of a sonar device in a reverberation-dominated region. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4140322 [Patent Document 2] JP 2015-165203 A [Patent Document 3] Patent No. 6220716 [Patent Document 4] Patent No. 5950573 [Patent Document 5] Patent No. 2845689 Summary of the Invention [Problem to be solved by the invention]

[0005] In order to increase the detection probability of underwater objects, it is necessary to determine optimal oscillation parameters. However, even when using the methods described in Patent Documents 1 to 5 above, there is a problem that the recommended oscillation parameters may not be suitable for detection depending on the posture and movement of the underwater object.

[0006] In view of the above problems, the present invention aims to provide an underwater object search support device, an underwater object search support method, and an underwater object search support program that can increase the detection probability by selecting optimal oscillation parameters. [Means for solving the problem]

[0007] An underwater object search support device according to one aspect of the present invention comprises: A wave transmitter that transmits an oscillating sound; a receiver for receiving a sound including a reverberation sound reflected from an underwater object; A signal processing unit that processes the acoustic data received by the receiver; a detection processing unit that detects echoes equal to or greater than a threshold from the signal-processed acoustic data and estimates the coordinates and movement track of the underwater object using the echoes; a prediction unit that predicts a detection probability based on a combination of the positions of the transmitter and the receiver and oscillation parameters; A storage unit that stores the detection probability data; a speed and course estimation unit that estimates the speed and course of the underwater object based on the coordinates and movement track of the underwater object; a wave transmitting / receiving position-specific Doppler shift estimating unit that estimates a Doppler shift of the underwater object for each combination of the wave transmitter and the wave receiver based on the speed and course of the underwater object; an ML estimation unit that determines whether the reverberation sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting and receiving position, and estimates an ML (masking level) based on the determination result; a TS estimation unit that estimates a TS (target strength) based on the course of the underwater object and the positions of the transmitter and receiver; an acquisition unit that acquires data on the detection probability at the coordinates of the underwater object from the storage unit; an update unit that updates the detection probability data based on the ML and TS; A selection unit that selects oscillation parameters based on the updated detection probability data; Equipped with.

[0008] A method for supporting an underwater object search according to one aspect of the present invention includes: A step of transmitting an oscillating sound; receiving a sound including a reverberation sound reflected from an underwater object; A step of signal processing the received acoustic data; detecting echoes equal to or greater than a threshold from the signal-processed acoustic data, and estimating the coordinates and movement track of the underwater object using the echoes; predicting a detection probability based on a combination of the transmitting and receiving positions and oscillation parameters; storing said probability of detection data; estimating a speed and a course of the underwater object based on the coordinates and the movement track of the underwater object; estimating a Doppler shift for each combination of the transmitting and receiving waves of the underwater object based on the speed and course of the underwater object; determining whether the reflected sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting and receiving position, and estimating a masking level (ML) based on the determination result; estimating a target strength (TS) based on the course of the underwater object and the positions of the transmitting and receiving waves; obtaining detection probability data at coordinates of the underwater object; updating the detection probability data based on the ML and TS; selecting oscillation parameters based on the updated detection probability data; Equipped with.

[0009] An underwater object search support program according to one aspect of the present invention includes: A step of transmitting an oscillating sound; receiving a sound including a reverberation sound reflected from an underwater object; A step of signal processing the received acoustic data; detecting echoes equal to or greater than a threshold from the signal-processed acoustic data, and estimating the coordinates and movement track of the underwater object using the echoes; predicting a detection probability based on a combination of the transmitting and receiving positions and oscillation parameters; storing said probability of detection data; estimating a speed and a course of the underwater object based on the coordinates and the movement track of the underwater object; estimating a Doppler shift for each combination of the transmitting and receiving waves of the underwater object based on the speed and course of the underwater object; determining whether the reflected sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting and receiving position, and estimating a masking level (ML) based on the determination result; estimating a target strength (TS) based on the course of the underwater object and the positions of the transmitting and receiving waves; obtaining detection probability data at coordinates of the underwater object; updating the detection probability data based on the ML and TS; selecting oscillation parameters based on the updated detection probability data; It is a program that allows a computer to process the above. Effect of the Invention

[0010] According to the present invention, it is possible to provide an underwater object search support device, an underwater object search support method, and an underwater object search support program that are capable of increasing the detection probability by selecting optimal oscillation parameters. [Brief description of the drawings]

[0011] [Figure 1] 1 is a block diagram of an underwater object search support device according to a first embodiment. [Diagram 2] FIG. 11 is a block diagram of an underwater object search support device according to a second embodiment. [Diagram 3] FIG. 11 is a detailed block diagram of a recommended oscillation parameter calculation unit of an underwater object search support device according to a second embodiment. [Figure 4] FIG. 11 is a diagram showing an example of detection probability map data according to the second embodiment. [Diagram 5] 8A to 8C are diagrams illustrating an example of a method for estimating the speed and course of an underwater object according to a second embodiment. [Figure 6] 8A to 8C are diagrams illustrating an example of a method for estimating the speed and course of an underwater object according to a second embodiment. [Figure 7] 8A to 8C are diagrams illustrating an example of a method for estimating the speed and course of an underwater object according to a second embodiment. [Figure 8] 10 is a spectrogram showing an example of a method for estimating a region of reverberation according to the second embodiment. [Figure 9] 13A to 13C are diagrams illustrating an example of a method for estimating an area of ​​reverberation according to the second embodiment. [Figure 10] FIG. 11 is a diagram showing an example of an angle-specific TS table according to the second embodiment. [Figure 11] FIG. 11 is a diagram showing an example of a detection probability table according to the second embodiment. [Figure 12] FIG. 11 is a diagram showing an example of a detection probability table according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] (Regarding related technology) First, a sonar device that assists in the search for underwater objects will be described. Sonar devices are broadly divided into passive sonar devices and active sonar devices. A passive sonar device is a device that captures sound waves generated by underwater objects in the water and calculates the presence of the underwater objects as well as their position and direction. In the present invention, underwater includes the water surface. For example, underwater objects include underwater creatures, submarines, and underwater mines.

[0013] On the other hand, an active sonar device is a device that emits (transmits) sound waves into the sea from a transmitter, detects the reflected sound (reverberation) from underwater objects with a receiver, and measures the position, distance, and speed of underwater objects from the time difference between the emitted sound and the reflected sound and the direction in which the reflected sound was detected. The received signal detected by the receiver includes echo signals, which are acoustic signals reflected from underwater objects, as well as reverberation, which is reflected sound from the sea surface and undersea topography, and surrounding noise.

[0014] Among active sonar devices, a multistatic sonar device is one in which the transmitter and receiver are located at separate positions. In a multistatic sonar device, for example, receivers can be installed at multiple positions for one transmitter. Naturally, multiple transmitters may be installed. In a multistatic sonar device, since the transmitter and receiver are located at separate positions, the received signal includes not only reflected sounds from underwater objects, but also sounds that propagate directly from the transmitter, called direct waves.

[0015] We will introduce an example of using sonobuoys in a multistatic sonar system with multiple receivers. A sonobuoy is an anti-submarine acoustic search device dropped by an aircraft that receives underwater acoustic signals and transmits radio waves to air traffic control. Among sonobuoys, a sonobuoy equipped only with a receiver is called a passive sonobuoy, and one equipped with a receiver and transmitter is called an active sonobuoy. A multistatic sonar system using sonobuoys is constructed by appropriately combining these two types of sonobuoys.

[0016] When sonar devices are used to aid in the search for underwater objects, reconnaissance is required. Reconnaissance refers to predicting the detection probability and detection distance of a sonar device in a search area based on the water temperature, underwater noise, and the characteristics of the sonar device in that area.

[0017] The detection probability of an active sonar device can be determined by the magnitude of the SE (signal excess) in the sonar equation shown below. SE can be calculated by finding each term on the right side of Equation 1 based on the performance values ​​of the sonar device and the respective ocean area and marine environment. (Formula 1) SE = SL - (TL1+TL2) - ML + DI + TS - DT SL Sound source level TL1 propagation loss (outbound) TL2 Propagation loss (return path) ML Masking Level DI directional gain TS Target Strength DT detection threshold Here, SL, DI, and DT are the performance parameters of the sonar device.

[0018] The detection probability can be calculated using formula 1. For example, assume that at a certain point, an underwater object can be detected with a detection probability of 100% when the SE is 10 or more. In this case, if the SE of a certain pulse is 5, the detection probability can be estimated to be 50% from the ratio of SEs. Note that, although an example of the calculation method has been presented, the calculation method is not limited to this.

[0019] ML (Masking Level) is a value used to mask the ambient noise (NL: Noise Level) that mixes in from around the receiver's wave receiving sensor, and the reverberation (RL: Reverberation Level) that occurs when the sound emitted by the sonar device reverberates in the surrounding area. Whether NL or RL becomes dominant depends on various factors such as the frequency and frequency band of the sound emitted by the sonar device, the pulse width, and the speed of underwater objects. In Equation 1, the appropriate SE can be obtained by masking the effects of NL and RL with ML.

[0020] TL (Propagation Loss) is the amount of loss when an oscillating sound propagates through water. The value of TL changes due to reflections from the seabed and ocean surface, and refraction in the water. TL also changes depending on the water temperature. Methods such as ray tracing are commonly used to calculate TL.

[0021] TS (Target Strength) is a measure of the area of ​​underwater objects detected by sonar equipment. In other words, TS is a parameter related to the volume of the echo when sound waves are reflected by an underwater object. TS is related to the frequency characteristics of the shape and material of the underwater object, and varies greatly depending on the angle of incidence and reflection of the sound waves on the object.

[0022] Sonar equipment selects conditions such as waveform, frequency, bandwidth, and pulse width, and emits a pulse. The waveform, bandwidth, and pulse width affect ML and DT, while the frequency affects TL and TS. With a pulse that has a constant frequency (PCW: Pulsed Continuous Wave), when the pulse width is large, the frequency resolution is excellent but the distance resolution is reduced. Also, when the pulse width is small, the frequency resolution is reduced but the distance resolution is excellent. When using a pulse with excellent frequency resolution, it becomes easier to separate reflected sounds from the reverberation frequency band, reducing the impact of reverberation on the search for underwater objects.

[0023] On the other hand, in the case of a pulse with a linear frequency change (LFM: Linear Frequency Modulation), the frequency bandwidth is related to the distance resolution, and the wider the frequency bandwidth, the better the distance resolution. However, since LFM does not have better frequency resolution than PCW, it is difficult to achieve the effect of reducing the effects of reverberation like PCW.

[0024] Here, two typical pulses are described, but the type of pulse to be selected depends on the propagation conditions of the oscillation sound in the search area and the underwater object to be searched. The operator must determine the optimal sensor placement and oscillation specifications based on the conditions of the sea area, the characteristics of the pulse, and the posture and movement of the underwater object. The oscillation specifications refer to the specifications of the performance, properties, features, etc. of the oscillation sound. Specifically, the specifications include the waveform, frequency, bandwidth, pulse width, etc., but other elements may also be used. The pulses used in the present invention are not limited to the pulses described above.

[0025] (First embodiment) Hereinafter, an embodiment of the present invention will be described with reference to the drawings. However, the present invention is not limited to the following embodiment. In addition, the following description and drawings are appropriately simplified for clarity of explanation.

[0026] 1 is a block diagram of an underwater object search support device 10 according to the first embodiment. The underwater object search support device 10 includes a wave transmitter 11, a wave receiver 12, a signal processing unit 13, a detection processing unit 14, a prediction unit 15, a memory unit 16, a speed and course estimation unit 17, a Doppler shift estimation unit for wave transmitting and receiving positions 18, an ML estimation unit 19, a TS estimation unit 20, an acquisition unit 21, an update unit 22, and a selection unit 23.

[0027] The wave transmitter 11 transmits an oscillating sound. The wave receiver 12 receives the sound including the echo sound reflected from the underwater object. The signal processor 13 performs signal processing on the acoustic data received by the wave receiver. The detection processor 14 detects echo sounds above a threshold from the signal-processed acoustic data, and estimates the coordinates and the moving track of the underwater object using the echo sounds. The prediction unit 15 predicts the detection probability in advance based on a combination of the positions of the wave transmitter and the wave receiver and the oscillation specifications. The memory unit 16 stores the detection probability data. The speed and course estimation unit 17 estimates the speed and course of the underwater object based on the coordinates and the moving track of the underwater object. The Doppler shift estimation unit 18 estimates the Doppler shift for each transmitting and receiving position of the underwater object for each combination of the wave transmitter and the wave receiver based on the speed and course of the underwater object. The ML estimation unit 19 judges whether the reflected sound belongs to the reverberation region or the noise region based on the Doppler shift for each transmitting and receiving position, and estimates the ML based on the judgment result. The TS estimation unit 20 estimates the TS based on the course of the underwater object and the positions of the transmitter and receiver. The acquisition unit 21 acquires detection probability data at the coordinates of the underwater object from the memory unit. The update unit 22 updates the detection probability data based on the ML and TS. The selection unit 23 selects the oscillation parameters based on the updated detection probability data. By including the above-mentioned components, the underwater object search support device 10 can select optimal oscillation parameters based on the detection probability of the underwater object taking into account ML and TS, thereby increasing the detection probability of the underwater object being searched for.

[0028] In the related art, depending on the posture and movement of the underwater object, the recommended oscillation specifications may not be suitable for detection. In all of the above-mentioned Patent Documents 1 to 5, it is assumed that the underwater objects are uniformly distributed within the search area, so that the representative values ​​or theoretical values ​​for TS and ML, which vary depending on the posture and movement of the underwater object, have to be used as provisional values. Depending on the magnitude of these parameters, SE may vary by 10 dB or more, and the detection probability will be greatly affected. In addition, the influence on TS and ML changes depending on the waveform, frequency, etc. of the oscillating pulse. Therefore, without considering TS and ML, there is a high possibility that oscillation specifications that are not suitable for detecting underwater objects will be recommended. According to the present invention, the values ​​of TS and ML are estimated and calculated using the sonar equation, so that the oscillation parameters can be determined taking TS and ML into consideration. This makes it possible to recommend and select oscillation parameters with higher accuracy, thereby increasing the probability of detecting underwater objects.

[0029] Second Embodiment 2 is a detailed block diagram of the underwater object search support device 100. Elements similar to those in the first embodiment are given the same reference numerals, and detailed explanations are omitted as appropriate. The wave transmitter 11 and the wave receiver 12 are omitted in FIG. 2. As shown in Figure 2, the underwater object search support device 100 of the second embodiment includes a signal processing unit 101, a detection processing unit 102, a display processing unit 103, a prediction unit 104, detection probability map data 105, a recommended oscillation parameter calculation unit 106, a sound source parameter input processing unit 107, an oscillation parameter input processing unit 108, and a control processing unit 109.

[0030] In the second embodiment, the signal processing unit 101, the detection processing unit 102, the prediction unit 104, and the detection probability map data 105 correspond to the signal processing unit 13, the detection processing unit 14, the prediction unit 15, and the storage unit 16 in the first embodiment, respectively. In addition, the function related to the recommended oscillation specifications calculation unit 106 corresponds to the functions related to the speed and course estimation unit 17, the Doppler shift estimation unit for each transmitting and receiving wave position 18, the ML estimation unit 19, the TS estimation unit 20, the acquisition unit 21, the update unit 22, and the selection unit 23 in the first embodiment. In addition, the display processing unit 103 is provided so that the operator can confirm the result in the detection processing unit 102 and operate it. In addition, in order to generate an oscillation sound after the selection of the oscillation specifications, a sound source specifications input processing unit 107, an oscillation specifications input processing unit 108, and a control processing unit 109 are provided.

[0031] FIG. 3 also shows a detailed configuration of the recommended oscillation parameters calculation unit 106 of the underwater object search support device 100 according to the second embodiment. The recommended oscillation parameters calculation unit 106 includes a speed and course estimation unit 110, a Doppler shift estimation unit for transmitting and receiving wave positions 111, an ML estimation unit 112, an angle-specific TS table 113, a TS estimation unit for transmitting and receiving wave positions 114, a detection probability table acquisition unit 115, a detection probability table update processing unit 116, and an oscillation parameters selection unit 117.

[0032] The components and operations of the underwater object search support device 100 will be described below with reference to FIGS. As shown in FIG. 2, a signal processor 101 performs signal processing on acoustic data including echoes from underwater objects. As a result of the signal processing, a detection processor 102 automatically detects echoes that are equal to or greater than a threshold. The detection processor 102 can calculate the coordinates, movement wake, and Doppler shift of the underwater object using the detected echoes. Specifically, the coordinates of the underwater object can be calculated from the time of oscillation from the transmitter, the time of reception of the echoes received by the receiver, and the direction of arrival of the echoes. In addition, the movement wake can be estimated by calculating the coordinates of the underwater object multiple times. The detection processor 102 estimates the Doppler shift based on the oscillation sound emitted from the transmitter and the echoes from the underwater object received by the receiver.

[0033] There are various methods for detecting echoes, including those that use the S / N (signal / noise) ratio and those that use machine learning. In order to display data related to the detected echo sound and estimated coordinates of the underwater object, the underwater object search support device 100 is preferably provided with a display processing unit 103. The operator can check the detection results of the acoustic data on the display processing unit 103. In addition, when multiple detection results are obtained, the detection information to be used may be manually selected.

[0034] The prediction unit 104 calculates the detection probability for all combinations of transmitter and receiver positions and oscillation parameters using environmental data such as water temperature structure and seabed topography, as well as actual search data, and stores the results in detection probability map data 105. Since the process of calculating the detection probability requires a large amount of calculation, it is preferable to perform the calculation before the start of the search.

[0035] The detection probability map data 105 is a database having, as map data, a prediction result calculated based on a combination of environmental data, coordinates of the transmitter and receiver (transmitting and receiving coordinates), and a plurality of oscillation parameters. FIG. 4 is an example of the detection probability map data 105. The map data shows the detection probability calculated for each coordinate based on the prediction result by the prediction unit 104. Specifically, as shown in the left diagram of FIG. 4, when the horizontal axis is the X axis and the vertical axis is the Y axis, the detection probability for each coordinate of the transmitter (transmitting buoy S1), the receiver (receiving R1), and the pulse type 1 is shown in the right diagram. For example, when (X,Y)=(1,1), the detection probability is 0%, when (X,Y)=(1,2), the detection probability is 20%, when (X,Y)=(2,1), the detection probability is 20%, and when (X,Y)=(2,2), the detection probability is 80%. In the following drawings of FIGS. 5 to 7 and 9, the horizontal axis is the X-axis and the vertical axis is the Y-axis.

[0036] The recommended oscillation parameters calculation unit 106 calculates optimal oscillation parameters based on the information of the detection processing unit 102 and the detection probability map data 105. A detailed configuration will be described later with reference to FIG. The sound source specification input processing unit 107 inputs a sound source to be used as an oscillation sound. The oscillation specification input processing unit 108 outputs the oscillation specifications input from the recommended oscillation specification calculation unit 106 and the sound source input from the sound source specification input processing unit 107 to the control processing unit 109. The control processing unit 109 applies control processing to the sound source based on the input oscillation specifications, and oscillates as a pulse. The pulse may be configured to be automatically oscillated.

[0037] A detailed configuration of the recommended oscillation parameters calculation unit 106 will be described with reference to Fig. 3. The speed and course estimation unit 110 estimates the speed and course of the underwater object based on the detection result of the detection processing unit 102. As a method of estimating the speed and course, as shown in Fig. 5, there is a method of estimating the speed and course of the underwater object from the displacement amount of coordinates obtained from detections at different times. Also, as shown in Fig. 6, a method of estimation using the coordinates and Doppler shift of the underwater object obtained from a single detection may be used. However, the estimation method is not limited to these, and other methods may be used.

[0038] 5 shows an example of a method for estimating the speed and course of an underwater object by the speed and course estimation unit 110, which estimates the speed and course of an underwater object from the displacement of coordinates estimated from the detection of echoes at different times. For example, the speed of the underwater object can be calculated from the detection coordinates (x1, y1) of the underwater object at time T1 and the detection coordinates (x2, y2) of the underwater object at time T2 using the target speed equation in FIG. 5. In addition, the course Θ of the underwater object (the slope of the line segment connecting the coordinates at time T1 and the coordinates at T2) can be calculated using the target course equation in FIG. 5.

[0039] FIG. 6 shows an example of a method for estimating the speed and course of an underwater object by the speed and course estimation unit 110, which estimates the speed and course of an underwater object from the coordinates of the underwater object and the Doppler shift calculated from the emitted sound and the reflected sound. For example, the speed and course of an underwater object can be calculated from the coordinates of the underwater object, the relative speed of the underwater object based on the Doppler shift detected by the wave receiving sensor R1 (relative speed of R1), and the relative speed of the underwater object based on the Doppler shift detected by the wave receiving sensor R2 (relative speed of R2). Although the case where there are two wave receiving sensors has been described, the target speed can be calculated in a similar manner even if there are two or more wave receiving sensors. Note that the relative speed here refers to the speed of the underwater object as seen from the wave receiving sensor.

[0040] Specifically, from Figure 7, if the relative speed of the underwater object based on the Doppler shift detected by wave receiving sensor R1 is 3 kt, the relative speed of the underwater object based on the Doppler shift detected by wave receiving sensor R2 is 3 kt, and the relative speed of the underwater object based on the Doppler shift detected by wave receiving sensor R3 is 0 kt, the movement speed of the underwater object can be calculated to be, for example, 5 kt. As described above, the speed and course estimation unit 110 can estimate the speed and course of an underwater object.

[0041] The Doppler shift estimation unit for wave transmitting / receiving positions 111 estimates the Doppler shift for each wave transmitting / receiving position obtained at the time of oscillation for each combination of wave transmitter and wave receiver from the speed and course obtained by the speed / course estimation unit 110 and the positional relationship of each wave transmitter and wave receiver. Note that the Doppler shift detected by the detection processing unit 102 is different from the Doppler shift for each wave transmitting / receiving position estimated by the Doppler shift estimation unit for wave transmitting / receiving positions 111. Specifically, the detection processing unit 102 estimates the Doppler shift from the oscillation sound actually generated by the wave transmitter and the echo sound actually received by the wave receiver. On the other hand, the Doppler shift estimation unit for wave transmitting / receiving positions 111 predicts, for example, how much Doppler shift the oscillation sound generated by a certain wave transmitter will be estimated as at a certain wave receiver from the speed and course of the underwater object obtained by the speed / course estimation unit 110 and the combination of all the wave transmitters and wave receivers. As shown in FIG. 3, the ML estimation unit 112 determines whether the Doppler shift for each transmitting / receiving position estimated by the transmitting / receiving position Doppler shift estimation unit 111 belongs to a reverberation region or a noise region, and estimates the ML based on the determination result.

[0042] The following describes a method by which the ML estimation unit 112 estimates whether the Doppler shift of the reverberation sound belongs to the reverberation region or the noise region. In Fig. 8, when the oscillation parameters are pulses oscillating at a constant frequency, reverberation and the reverberation sound are displayed on a spectrogram with the horizontal axis representing time and the vertical axis representing frequency. Since the Doppler shift of the reverberation is small, it appears in the reverberation region, which is close to the frequency of the oscillation sound. As shown in Fig. 8, if the frequency band of the reverberation sound belongs to the noise region, the effect of noise can be reduced by using NL as ML, and a more accurate SE can be obtained.

[0043] The magnitude of the Doppler shift is determined by the speed of the transmitting and receiving waves, and the underwater object. Therefore, the ML estimation unit 112 determines whether the reflected sound belongs to the reverberation region or the noise region at each receiving sensor, and estimates the ML. For example, when the receiving sensor R1 in FIG. 9 receives the reflected sound, it is assumed that the relative speed based on the assumed Doppler shift is about 2 kt. If the width of the relative speed based on the reverberation frequency bandwidth is set to ±1.5 kt, the reflected sound detected by the receiving sensor R1 is determined to be received in the noise region. In this case, the noise NL is used as the ML.

[0044] On the other hand, if the relative velocity based on the assumed Doppler shift when the reflected sound is received at the point of the receiving sensor R2 is assumed to be 0 kt, and the width of the relative velocity based on the reverberation frequency bandwidth is set to ±1.5 kt, the reflected sound detected by the receiving sensor R2 is determined to be received in the reverberation region. In this case, the reverberation RL is used as ML.

[0045] As described above, the ML estimation unit 112 compares the estimated Doppler shift for each transmitter / receiver position and the reverberation frequency bandwidth for each combination of transmitter / receiver and oscillation parameters, and determines whether the reflected sound belongs to the reverberation region or the noise region. Based on the determination result, it estimates either NL or RL as ML, and outputs the updated ML value to the detection probability table update processing unit 116.

[0046] In addition, when the prediction unit 104 has obtained estimated values ​​of RL and NL according to time and distance, the ML may be estimated from the previously estimated RL and NL. In this case, the ML can be estimated in advance without requiring information such as reverberation. Either the reverberation RL or the noise NL may be estimated as the ML, or the sum of the two may be used. Instead of the ML estimated value of the prediction unit 104, a reverberation area may be set based on the result of signal processing in the signal processing unit 101, and the reverberation area may be used as a reference object of the ML estimation unit 112.

[0047] The angle-specific TS table 113 shown in FIG. 3 is a table including TS data for each angle. 10 is a schematic diagram showing the TS for each angle stored in the angle-specific TS table 113. For example, data is stored assuming the TS for each angle of an underwater object, with the TS being 10 dB at an angle of 0°, the TS being 15 dB at an angle of 10°, and the TS being 20 dB at an angle of 20°.

[0048] If the underwater object is a perfect sphere, the TS will be the same in any direction, but if the underwater object has a wide reflecting surface at a specific angle, the TS will be large in that direction. The accuracy of the estimated TS value can be improved by storing in advance data on the TS of the underwater object as shown in FIG. 10 in the device and returning the TS of the corresponding angle in response to a call from the transmitting / receiving position specific TS estimator 114. Specifically, if the TS for each angle of the underwater object is known or can be estimated, the angle specific TS table 113 storing the TS for each angle can be used. Furthermore, a configuration may be used in which multiple tables are stored according to the type and number of underwater objects expected. If the TS of the underwater object is not known or can be estimated, a fixed value of TS may be set.

[0049] The TS of an underwater object can also be estimated as follows. The wave transmitting / receiving position specific TS estimator 114 estimates the TS of the target for each position of the wave transmitter and the wave receiver. A simple estimation method is to use a bisector of the wave transmitting / receiving position and three points of the coordinates of the underwater object. In the case of a multistatic sonar device, the wave transmitting / receiving position specific TS estimator 114 can estimate the TS by referring to the angle specific TS table 113, assuming that the wave transmitter and the wave receiver are located on a line that bisects the angle between the coordinates of the underwater object and the positions of the wave transmitter and the wave receiver with respect to the course of the underwater object as the angle of incidence of the generated sound to the underwater object. The TS estimation method is not limited to this, and other methods such as a method of calculation from the theoretical formula of the Doppler effect may be used.

[0050] The detection probability table acquisition unit 115 acquires the detection probability at the coordinates of the underwater object from the detection probability map data 105 as a detection probability table.

[0051] A detection probability table update processing unit 116 updates the detection probability table acquired by the detection probability table acquisition unit 115 using the ML and TS calculated by the ML estimation unit 112 and the TS estimation unit for each transmitting and receiving position 114 .

[0052] Fig. 11 is an example of a detection probability table. The items in the table are, for example, the transmitted sound source from the transmitting buoy, the receiving sensor, the pulse type, the reverberation sound, and TS, ML, and detection probability estimated based on the position and pulse type of the transmitter and receiver. The first row is the transmitted sound source S1, the receiving sensor R1, pulse 1, TS1, and ML1(RL), and the detection probability is P(1,1,1). A specific example will be explained with Fig. 12. Here, ML1(RL) is the case where the reverberation sound belongs to the reverberation region, and indicates that RL is used for ML.

[0053] Fig. 12 is an example of a detection probability table in which the detection probability is arranged in descending order from the first row of the table. As shown in Fig. 12, the transmitted sound source S1, the receiving sensor R1, the pulse 2, the TS1, and the ML2 (NL) in the first row have the highest detection probability of 80%. The arrangement shown in Fig. 12 is an example and is not limited to this.

[0054] The oscillation parameter selection unit 117 selects oscillation parameters to be oscillated from the detection probability table updated using TS and ML. For example, when recommending oscillation parameters with a high detection probability, pulse 2 with the highest detection probability of 80% is selected as the recommended oscillation parameters as shown in FIG. 12. The oscillation parameter selection unit 117 outputs pulse 2 to the oscillation parameter input processing unit 108 as the recommended oscillation parameters. Note that the oscillation parameters with the highest detection probability may be output to the oscillation parameter input processing unit 108 in order. For example, when an algorithm for maximizing the detection probability is used, the detection probability table updated with the detection probability using TS and ML may be searched for the oscillation parameters with the highest detection probability, and the oscillation parameters may be output as the recommended oscillation parameters. When there are multiple oscillation parameters with the same detection probability, the oscillation parameters with the highest distance resolution may be selected based on the pulse characteristics. Moreover, the automatic oscillation by the oscillation parameter input processing unit 108 can be designed so that it can be turned on and off by an operator.

[0055] Since there are multiple criteria for selecting the oscillation parameters depending on the situation, it is preferable that the conditions of the oscillation parameters are programmable. The oscillation parameters selected may be one optimum one, or may include all parameters that satisfy the conditions. The oscillation parameter selection unit 117 may be configured to assign a priority to the detection probability data based on at least one of the detection probability, TS, ML, and distance resolution of the pulse type, and select the oscillation parameters based on the priority.

[0056] If new echoes are detected after all oscillations based on the oscillation parameters selected by the oscillation parameter selection unit 117 have been completed, the recommended oscillation parameter calculation unit 106 may be configured to determine the next recommended oscillation parameters again. In addition, the recommended oscillation parameter calculation unit 106 may determine the next oscillation parameters based on the latest detection of echoes before all oscillations have been completed by simultaneously performing multiple processes such as the processing in the control processing unit 109 and the detection processing unit 102. This function may be configured to continue updating the recommended oscillation parameters based on the detected information and continue oscillation unless detection by the detection processing unit 102 has been completed or an operator gives an instruction to stop.

[0057] As described above, the present invention can provide an underwater object search support device, an underwater object search support method, and an underwater object search support program that enable selection of optimal oscillation parameters by taking ML and TS into consideration, thereby increasing the detection probability.

[0058] In addition, in the related art, the process from determining the oscillation parameters to operating the oscillation had to be done manually, which took time. If the underwater object being searched for took evasive action such as changing course or depth, the parameters in the sonar equation would change at the next oscillation, and detection may not have been achieved. According to the present invention, it is possible to automate the process from determining the oscillation parameters to operating the oscillation. This solves the problem of being unable to respond to the target's sudden actions. In other words, the time required for human confirmation and judgment is no longer necessary, and the probability of losing sight of the underwater object can be reduced. The present invention can be used in search support devices for underwater objects, and can also be used in, for example, automatic underwater object search and tracking programs using unmanned aerial vehicles, autonomous sensor systems, and sensor networks.

[0059] In the above example, various control programs can be stored and supplied to a computer using various types of non-transitory computer readable media. The non-transitory computer readable media includes various types of tangible storage media. Examples of the non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs, CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs). The programs may also be supplied to a computer by various types of transitory computer readable media. Examples of the transitory computer readable media include electric signals, optical signals, and electromagnetic waves. The transitory computer readable media can supply the programs to a computer via wired communication paths such as electric wires and optical fibers, or wireless communication paths.

[0060] The present invention is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit and scope of the present invention. [Explanation of symbols]

[0061] 10 Underwater object search support device 11 Transmitter 12 Receiver 13 Signal Processing Section 14 Detection processing section 15 Forecast Department 16 Memory section 17 Speed ​​and Course Estimation Section 18. Doppler shift estimation section for each transmitting and receiving position 19 ML estimation part 20 TS Estimation Section 21 Acquisition Department 22 Update section 23 Selection section 100 Underwater object search support device 101 Signal processing section 102 Detection processing unit 103 Display processing unit 104 Forecast Department 105 Detection Probability Map Data 106 Recommended oscillation specifications calculation section 107 Sound source specification input processing unit 108 Oscillation parameter input processing unit 109 Air Traffic Control Department 110 Speed ​​and Course Estimation Unit 111 Doppler shift estimation unit for each transmitting and receiving position 112 ML estimation part 113 TS table by angle 114 TS Estimation Unit for Each Transmitting and Receiving Position 115 Detection Probability Table Acquisition Unit 116 Detection probability table update processing unit 117 Oscillation parameter selection section

Claims

1. One or more wave transmitters that transmit an oscillating sound; A plurality of receivers for receiving sounds including echoes reflected from underwater objects from the oscillation sound; A signal processing unit that processes the acoustic data received by the receiver; a detection processing unit that detects echoes equal to or greater than a threshold from the signal-processed acoustic data and estimates the coordinates and movement track of the underwater object using the echoes; A prediction unit that predicts a detection probability for each coordinate based on a combination of the positions of the transmitter and the receiver and oscillation parameters; a storage unit that stores all of the detection probability data predicted by the prediction unit as detection probability map data for each combination of the transmitter, the receiver, and the oscillation parameters; a speed and course estimation unit that estimates the speed and course of the underwater object based on the coordinates and movement track of the underwater object; a wave transmitting / receiving position-specific Doppler shift estimating unit that estimates a Doppler shift of the underwater object for each combination of the wave transmitter and the wave receiver based on the speed and course of the underwater object; an ML estimation unit that determines whether the reverberation sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting and receiving position, and determines the reverberation as an ML (masking level) when the reverberation sound belongs to the reverberation region, and determines the noise as an ML when the reverberation sound belongs to the noise region; a TS estimator that estimates a TS (target strength) for each position of the wave transmitter and the wave receiver based on a course of the underwater object and the positions of the wave transmitter and the wave receiver; an acquisition unit that acquires, from the detection probability map data stored in the storage unit, data on the detection probability for each combination of the transmitter, the receiver, and the oscillation parameters at the coordinates of the underwater object as a detection probability table; an update unit that updates the detection probability table acquired by the acquisition unit based on the ML determined by the ML estimation unit and the TS estimated by the TS estimation unit; A selection unit that selects oscillation parameters based on the updated detection probability table; Equipped with Underwater object search support device.

2. One or more wave transmitters that transmit an oscillating sound; A plurality of receivers for receiving sounds including echoes reflected from underwater objects from the oscillation sound; A signal processing unit that processes the acoustic data received by the receiver; a detection processing unit that detects echoes equal to or greater than a threshold from the signal-processed acoustic data and estimates the coordinates and Doppler shift of the underwater object using the echoes; A prediction unit that predicts a detection probability for each coordinate based on a combination of the positions of the transmitter and the receiver and oscillation parameters; a storage unit that stores all of the detection probability data predicted by the prediction unit as detection probability map data for each combination of the transmitter, the receiver, and the oscillation parameters; a speed and course estimation unit that estimates the speed and course of the underwater object based on the coordinates and Doppler shift of the underwater object; a wave transmitting / receiving position-specific Doppler shift estimating unit that estimates a Doppler shift of the underwater object for each combination of the wave transmitter and the wave receiver based on the speed and course of the underwater object; an ML estimation unit that determines whether the reverberation sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting and receiving position, and determines the reverberation as an ML (masking level) when the reverberation sound belongs to the reverberation region, and determines the noise as an ML when the reverberation sound belongs to the noise region; a TS estimator that estimates a TS (target strength) for each position of the wave transmitter and the wave receiver based on a course of the underwater object and the positions of the wave transmitter and the wave receiver; an acquisition unit that acquires, from the detection probability map data stored in the storage unit, data on the detection probability for each combination of the transmitter, the receiver, and the oscillation parameters at the coordinates of the underwater object as a detection probability table; an update unit that updates the detection probability table acquired by the acquisition unit based on the ML determined by the ML estimation unit and the TS estimated by the TS estimation unit; A selection unit that selects oscillation parameters based on the updated detection probability table; Equipped with Underwater object search support device.

3. The storage unit stores TS data for each angle when the TS of the underwater object is known or can be estimated, The TS estimation unit estimates a TS based on the TS data for each angle.

3. An underwater object search support device according to claim 1 or 2.

4. The TS estimation unit determines the angle of incidence of the oscillation sound to the underwater object as the TS angle when it is assumed that the wave transmitter and the wave receiver are located on a line that bisects an angle between the coordinates of the underwater object and the positions of the wave transmitter and the wave receiver relative to the course of the underwater object, Querying the angle-specific TS data to estimate TS; 4. An underwater object search support device according to claim 3.

5. the detection probability table includes data on the detection probability, the TS, the ML, and a pulse type, the selection unit assigns a priority to the detection probability data included in the updated detection probability table based on at least one of the detection probability, the TS, the ML, and the distance resolution of the pulse type, and selects oscillation parameters based on the priority.

5. An underwater object search support device according to claim 1.

6. an oscillation parameter input processing unit that performs input processing of the oscillation parameters selected by the selection unit; and a control processing unit that performs control processing on the selected transducer based on the oscillation parameters input and processed by the oscillation parameter input processing unit, automatically oscillating the oscillation sound of the selected oscillation parameters; 6. An underwater object search support device according to claim 1.

7. A step of transmitting an oscillating sound from one or more wave transmitters; receiving, by a plurality of receivers, sounds including echoes reflected from underwater objects by the oscillating sound; A step of signal processing the received acoustic data; detecting echoes equal to or greater than a threshold from the signal-processed acoustic data, and estimating the coordinates and movement track of the underwater object using the echoes; A step of predicting a detection probability for each coordinate based on a combination of the positions of the transmitter and the receiver and the oscillation parameters; storing all of the predicted detection probability data as detection probability map data for each combination of the transmitter, the receiver, and the oscillation parameters; estimating a speed and a course of the underwater object based on the coordinates and the movement track of the underwater object; estimating a Doppler shift for each transmitting and receiving position of the underwater object for each combination of the transmitter and the receiver based on the speed and course of the underwater object; determining whether the reflected sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting / receiving position, and determining the reverberation as ML (masking level) if the reflected sound belongs to the reverberation region, and determining the noise as ML if the reflected sound belongs to the noise region; estimating a target strength (TS) for each position of the transmitter and the receiver based on the course of the underwater object and the positions of the transmitter and the receiver; acquiring, from the stored detection probability map data, data on the detection probability for each combination of the transmitter, the receiver, and the oscillation parameters at the coordinates of the underwater object as a detection probability table; updating the obtained detection probability table based on the determined ML and the estimated TS; selecting oscillation parameters based on the updated detection probability table; Equipped with A method for assisting in the search for underwater objects.

8. A step of transmitting an oscillating sound from one or more wave transmitters; receiving, by a plurality of receivers, sounds including echoes reflected from underwater objects by the oscillating sound; A step of signal processing the received acoustic data; detecting echoes equal to or greater than a threshold from the signal-processed acoustic data, and estimating the coordinates and movement track of the underwater object using the echoes; A step of predicting a detection probability for each coordinate based on a combination of the positions of the transmitter and the receiver and the oscillation parameters; storing all of the predicted detection probability data as detection probability map data for each combination of the transmitter, the receiver, and the oscillation parameters; estimating a speed and a course of the underwater object based on the coordinates and the movement track of the underwater object; estimating a Doppler shift for each transmitting and receiving position of the underwater object for each combination of the transmitter and the receiver based on the speed and course of the underwater object; determining whether the reflected sound belongs to a reverberation region or a noise region based on the Doppler shift for each transmitting / receiving position, and determining the reverberation as ML (masking level) if the reflected sound belongs to the reverberation region, and determining the noise as ML if the reflected sound belongs to the noise region; estimating a target strength (TS) for each position of the transmitter and the receiver based on the course of the underwater object and the positions of the transmitter and the receiver; acquiring, from the stored detection probability map data, data on the detection probability for each combination of the transmitter, the receiver, and the oscillation parameters at the coordinates of the underwater object as a detection probability table; updating the obtained detection probability table based on the determined ML and the estimated TS; selecting oscillation parameters based on the updated detection probability table; An underwater object search support program that allows a computer to process the above information.

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