Passive sonar network monitoring system based on underwater unmanned aerial vehicle group

Abstract

The invention provides a passive sonar network monitoring system based on an underwater unmanned aerial vehicle group. The passive sonar network monitoring system comprises a plurality of unmanned aerial vehicles distributed underwater and a sonar monitoring module for sonar monitoring underwater, the fixing module is used for matching and fixing the sonar monitoring module and the unmanned aerial vehicle; and the control station is arranged on the water and is used for analyzing and processing sound wave signals obtained by monitoring of the sonar monitoring module. The control station disclosed by the invention realizes efficient and accurate underwater sound source monitoring and analysis by receiving and filtering various sound wave signals, extracting a target frequency spectrum band by utilizing Fourier transform, analyzing the signals in detail to determine the type of a sound source, summarizing position information and monitoring time of different sensors, splicing the monitoring time and generating a moving track.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean sonar monitoring systems, and in particular to a passive sonar network monitoring system based on a group of underwater drones. Background Art

[0002] Sonar is an electronic device that uses the propagation characteristics of sound waves underwater to complete underwater detection and communication tasks through electroacoustic conversion and information processing. It has two types: active and passive, and belongs to the category of acoustic positioning. Sonar is an electronic device that uses underwater sound waves to detect, locate and communicate with underwater targets. It is the most widely used and important device in hydroacoustics. Underwater drones refer to drone systems that can operate autonomously and perform tasks underwater. They are usually equipped with sensors, cameras, robotic arms and other equipment, and can perform various tasks underwater, such as seabed exploration, underwater topography mapping, and target search. The group operation of underwater drones can improve monitoring efficiency and coverage. The passive sonar network consists of multiple passive sonar nodes distributed in the ocean, which monitor the marine environment and underwater targets by receiving sounds in the water.

[0003] This experimental team has been browsing and researching a large amount of relevant records and materials on the relevant technologies of ocean sonar for a long time. At the same time, it relies on relevant resources and conducts a large number of relevant experiments. After a lot of searches, it is found that existing technologies such as CN116879905B, CN110865379B, CN117135732B, and CN106886015B disclosed in the prior art are found. For example, the prior art discloses a wake-up system based on a submersible device, which involves the field of marine engineering technology. The system includes: an electromagnetic wave ringing wake-up module, which is used to receive a cruise wireless signal of a set frequency sent by a pre-programmed watercraft, and wake up the first submersible device in response to the received cruise wireless signal; a passive sonar wake-up module, which is used to receive a hull sonar signal sent by the first ship, and wake up the first submersible device in response to the received hull sonar signal; the passive sonar wake-up module is also used to receive a towed sonar signal sent by a carrier platform, and wake up the first submersible device in response to the received towed sonar signal; an anchoring module, which is connected to the first submersible device, and is used to anchor the first submersible device on the seabed. This application solves the technical problem of low wake-up efficiency of submersible devices.

[0004] The present invention is made to solve the common problems in the field such as low efficiency in identifying and tracking underwater sound sources. Summary of the invention

[0005] The purpose of the present invention is to propose a passive sonar network monitoring system based on a group of underwater drones in response to the shortcomings currently existing in the field.

[0006] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0007] A passive sonar network monitoring system based on a group of underwater drones, the passive sonar network monitoring system comprises a plurality of drones distributed underwater, a sonar monitoring module for performing sonar monitoring underwater, a fixing module for adapting and fixing the sonar monitoring module to the drones, and a control station arranged above water for analyzing and processing the sound wave signals monitored by the sonar monitoring module.

[0008] Among them, the drone, sonar monitoring module and control station are connected through communication technology signals. The drone includes a positioning system that is integrated with GPS, INS, acoustic positioning, visual positioning and depth sensors.

[0009] Several drones are used to drop the sonar monitoring module underwater and to recover the underwater sonar monitoring module.

[0010] The sonar monitoring module includes a plurality of monitoring units, each of which includes a shell with a plate-like structure, sonar sensors distributed in a matrix on the top wall of the shell, a counterweight fixed to the bottom of the shell, a positioner arranged in the shell, and a storage device for storing the monitoring data of the sonar sensor. The shell is a sealed and waterproof structure, and the interior of the shell is an airtight cavity.

[0011] Furthermore, the underwater area is evenly divided into several operation areas, each of which has at least one drone and several monitoring units.

[0012] The sonar sensor continuously receives sound signals from the underwater environment, and all sound signals received by the sonar sensor are recorded and stored in the memory, waiting to be further transmitted to the drone.

[0013] The drone moves underwater and periodically transmits the monitoring data of all monitoring units in the same operation area in batches.

[0014] The drone regularly rises to the surface to send monitoring data to the control station.

[0015] Furthermore, the fixing module includes a permanent magnet fixed in the shell, and an adsorption unit fixed on the body of the drone and used to generate an adsorption magnetic force on the permanent magnet and thereby adsorb and fix the shell.

[0016] Furthermore, the adsorption unit includes an airtight box, an electromagnetic coil installed in the box, a controller for controlling the current of the electromagnetic coil to control the electromagnetic adsorption strength of the electromagnetic coil to the permanent magnet, and a locking part for fixing the airtight box to the drone.

[0017] Furthermore, the operation contents of placing the monitoring unit by the drone include:

[0018] The drone determines its current position through its own positioning system, and moves to the designated monitoring unit placement area according to the predetermined operation area division method and the instructions issued by the control station.

[0019] After reaching the designated location, the drone releases the magnetic adsorption of the monitoring unit through the adsorption unit in its fixed module, allowing the monitoring unit to descend to the underwater target location through gravity.

[0020] After the monitoring unit reaches the underwater target position, it performs position calibration through the internal locator to ensure that the monitoring unit is stably and accurately placed at the predetermined position, and then starts sonar monitoring.

[0021] Furthermore, the operation of the drone to recover the underwater monitoring unit includes:

[0022] The drone maintains regular contact with each monitoring unit through communication technology and receives the status data of the monitoring unit, including power supply and integrity data of the monitoring data. When the drone receives a message that a monitoring unit is short of power or the monitoring data is incomplete, it immediately records the location of the monitoring unit and notifies the control station.

[0023] The UAV moves to the location of the faulty monitoring unit according to the recorded location and the instructions of the control station. The adsorption unit of the UAV is activated, and the magnetic force is generated by controlling the current of the electromagnetic coil to adsorb and fix the faulty monitoring unit to the UAV body. The UAV drives the monitoring unit to gradually float to the surface of the water, so as to bring the faulty monitoring unit back to the ground for maintenance or replacement of the power supply.

[0024] Furthermore, the control station implements the following operation steps:

[0025] S101: receiving a sound wave signal received by a drone, the sound wave signal including sound waves from different sound sources, the different sound sources including ships, marine life and natural sounds,

[0026] S102: Filter the monitoring signal using a filter.

[0027] S103: Convert the filtered time-domain sound wave signal into a frequency-domain signal by Fourier transform, and then extract a frequency spectrum segment within a preset frequency range [Fre1, Fre2] from the frequency-domain signal as a target signal.

[0028] S104: Analyze the extracted target signals to determine the sound source type corresponding to each target signal.

[0029] S105: The location information and monitoring time of the same sound source received from different sonar sensors are analyzed.

[0030] The lines are summarized to form comprehensive sound source information.

[0031] S106: Continuously splicing the monitoring time, and further extracting and generating the movement trajectory of the sound source during the continuous monitoring time according to the position change of the sonar sensor during the continuous monitoring time.

[0032] The beneficial effects achieved by the present invention are:

[0033] 1. The passive sonar network monitoring unit of the present invention has the advantages of flexible deployment, efficient recovery, wide coverage, real-time monitoring and data transmission, high degree of automation, reasonable structural design, precise positioning, energy saving and high efficiency, rapid response to faults and reduced labor costs, making it an efficient, flexible and reliable underwater monitoring solution suitable for various application scenarios such as environmental monitoring, resource exploration and security monitoring.

[0034] 2. The control station of the present invention realizes efficient and accurate underwater sound source monitoring and analysis by receiving and filtering multiple sound wave signals, extracting target spectrum segments using Fourier transform, analyzing signals in detail to determine the type of sound source, summarizing the location information and monitoring time of different sensors, splicing the monitoring time and generating movement trajectories.

[0035] 3. The present invention extracts the maximum peak and spectrum characteristics by traversing the target signal, calculates the total energy, frequency distribution mean, discrete distribution, centroid value, shape characteristics, energy normalization and energy distribution characteristic value, and combines the pre-collected multi-type sound source samples for comprehensive characteristic value matching, thereby achieving efficient and accurate underwater sound source identification and classification, thereby ensuring the reliability, accuracy and real-time response capability of the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0037] Figure 1 It is a modular schematic diagram of the passive sonar network monitoring system based on underwater drone groups of the present invention.

[0038] Figure 2 It is a schematic diagram of the operation flow of the control station of the present invention.

[0039] Figure 3 It is a schematic diagram of the process of establishing a sample library of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention is further described in detail in combination with its embodiments below; it should be pointed out that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present case. For those skilled in the art, after reviewing the following detailed description, other systems, methods and / or features of this embodiment will become apparent. And the terms describing the positional relationship in the accompanying drawings are only used for illustrative purposes and cannot be understood as limitations on this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to the specific circumstances.

[0041] Embodiment 1: Combining with Figure 1 , Attachment Figure 2 , and attached Figure 3 This embodiment constructs a passive sonar network monitoring system based on a group of underwater drones. The passive sonar network monitoring system includes a number of drones distributed underwater, a sonar monitoring module for performing sonar monitoring underwater, a fixing module for adapting and fixing the sonar monitoring module to the drones, and a control station arranged above water for analyzing and processing the sound wave signals monitored by the sonar monitoring module.

[0042] Among them, the drone, sonar monitoring module and control station are connected through communication technology signals. The drone includes a positioning system that is integrated with GPS, INS, acoustic positioning, visual positioning and depth sensors.

[0043] Several drones are used to drop the sonar monitoring module underwater and to recover the underwater sonar monitoring module.

[0044] The sonar monitoring module includes a plurality of monitoring units, each of which includes a plate-shaped shell, sonar sensors arranged in a matrix on the shell top wall, a counterweight fixed to the bottom of the shell, a positioner arranged in the shell, and a storage device for storing the monitoring data of the sonar sensor. The shell is a sealed and waterproof structure, and the interior of the shell is an airtight cavity.

[0045] The underwater area is evenly divided into several operation areas, each of which has at least one drone and several monitoring units.

[0046] The sonar sensor continuously receives sound signals from the underwater environment, and all sound signals received by the sonar sensor are recorded and stored in the memory, waiting to be further transmitted to the drone.

[0047] The drone moves underwater and periodically transmits the monitoring data of all monitoring units in the same operation area in batches.

[0048] The drone regularly rises to the surface to send monitoring data to the control station.

[0049] The fixing module includes a permanent magnet fixed in the shell, and an adsorption unit fixed on the body of the drone and used to generate an adsorption magnetic force on the permanent magnet to adsorb and fix the shell.

[0050] The adsorption unit includes an airtight box, an electromagnetic coil installed in the box, a controller for controlling the current of the electromagnetic coil to control the electromagnetic adsorption strength of the electromagnetic coil to the permanent magnet, and a locking member for fixing the airtight box to the drone.

[0051] The operation content of placing the monitoring unit by drone:

[0052] The drone determines its current position through its own positioning system, and moves to the designated monitoring unit placement area according to the predetermined operation area division method and the instructions issued by the control station.

[0053] After reaching the designated location, the drone releases the magnetic adsorption of the monitoring unit through the adsorption unit in its fixed module, allowing the monitoring unit to descend to the underwater target location through gravity.

[0054] After the monitoring unit reaches the underwater target position, it performs position calibration through the internal positioner to ensure that the monitoring unit is stably and accurately arranged at the predetermined position, and then starts sonar monitoring;

[0055] The operation content of the drone to recover the underwater monitoring unit:

[0056] The drone maintains regular contact with each monitoring unit through communication technology and receives the status data of the monitoring unit, including power supply and integrity data of the monitoring data. When the drone receives a message that a monitoring unit is short of power or the monitoring data is incomplete, it immediately records the location of the monitoring unit and notifies the control station.

[0057] The drone moves to the location of the faulty monitoring unit according to the recorded location and the command of the control station. The adsorption unit of the drone is activated, and the magnetic force is generated by controlling the current of the electromagnetic coil to adsorb and fix the faulty monitoring unit to the drone body. The drone drives the monitoring unit to gradually float to the surface of the water, so as to bring the faulty monitoring unit back to the ground for maintenance or replacement of the power supply.

[0058] The passive sonar network monitoring unit of the present invention has the advantages of flexible deployment, efficient recovery, wide coverage, real-time monitoring and data transmission, high degree of automation, reasonable structural design, precise positioning, energy saving and high efficiency, rapid response to faults and reduced labor costs, making it an efficient, flexible and reliable underwater monitoring solution suitable for a variety of application scenarios such as environmental monitoring, resource exploration and security monitoring.

[0059] Embodiment 2: Combining with Figure 1, Attachment Figure 2 , and attached Figure 3 In addition to the contents of the above embodiments, the control station also implements the following operation steps:

[0060] S101: receiving a sound wave signal received by a drone, the sound wave signal including sound waves from different sound sources, the different sound sources including ships, marine life and natural sounds,

[0061] S102: Filter the monitoring signal using a filter.

[0062] S103: Convert the filtered time-domain sound wave signal into a frequency-domain signal by Fourier transform, and then extract a frequency spectrum segment within a preset frequency range [Fre1, Fre2] from the frequency-domain signal as a target signal.

[0063] S104: Analyze the extracted target signals to determine the sound source type corresponding to each target signal.

[0064] S105: The location information and monitoring time of the same sound source received from different sonar sensors are analyzed.

[0065] The lines are summarized to form comprehensive sound source information.

[0066] S106: Continuously splicing the monitoring time, and further extracting and generating the movement trajectory of the sound source during the continuous monitoring time according to the position change of the sonar sensor during the continuous monitoring time,

[0067] The control station of the present invention realizes efficient and accurate underwater sound source monitoring and analysis by receiving and filtering multiple sound wave signals, extracting target spectrum segments using Fourier transform, analyzing signals in detail to determine the type of sound source, summarizing the location information and monitoring time of different sensors, splicing the monitoring time and generating movement trajectories.

[0068] Embodiment 3: Combining with Figure 1 , Attachment Figure 2 , and attached Figure 3 In addition to the contents of the above embodiments, the method of analyzing the extracted target signal in step S104 to determine the type of sound source corresponding to the extracted target signal is as follows:

[0069] S1041: traverse the target signal to obtain the frequency value Fmax corresponding to the maximum peak point in the frequency spectrum of the target signal, where Amax is the amplitude value of the signal at the frequency point Fmax of the target signal.

[0070] S1042: Calculate the total energy Ena in the target frequency:

[0071]

[0072] Wherein, Fre represents the independent variable of the frequency spectrum in the target signal, X(Fre) represents the signal amplitude at the frequency Fre, Fre∈[Fre1, Fre2], |X(Fre)| represents the absolute value of the signal amplitude at the frequency Fre in the target signal;

[0073] S1043: Calculate the frequency distribution mean Favg:

[0074]

[0075] S1044: Obtain the frequency discrete distribution characteristic value Disp of the target signal:

[0076]

[0077] S1045: Obtain the spectrum centroid value Cent of the target signal:

[0078]

[0079] S1046: Obtain the spectrum shape characteristic value Sv of the target signal:

[0080]

[0081] S1047: Calculate the energy normalization value EFR:

[0082]

[0083] S1048: Calculate the energy distribution characteristic value Han used to reflect the signal spectrum:

[0084]

[0085] lnX(Fre) represents the natural logarithm of the signal amplitude corresponding to the frequency Fre.

[0086] S1049: Calculate the comprehensive characteristic value Fcp of the target signal:

[0087] Fcp=A1×Fmax+A2×Favg+A3×Disp+A4×Cent+A5×Sv+A6×Han, A1 is the weight value of Fmax, and the value range of A1 is 0.05-0.1, A2 is the weight value of Favg, and the value range of A2 is 0.1-0.15, A3 is the weight value of Disp, and the value range of A3 is 0.15-0.25, A4 is the weight value of Cent, and the value range of A4 is 0.15-0.2,

[0088] A5 is the weight value of Sv, and the value range of A5 is 0.2-0.3.

[0089] A6 is the weight value of Han, and the value range of A6 is 0.1-0.2.

[0090] And A1+A2+A3+A4+A5+A6=1,

[0091] S1049: inputting Fcp into a value sample library, and determining a sound source in the sample library that matches Fcp as a sound source of the target signal;

[0092] The sample library is stored in the control station, and the sample library is established as follows:

[0093] S201: pre-collecting sound samples of different types of sound sources, where the different types of sound sources at least include sounds of ships, marine life and nature, and calculating Fcp of each sound sample.

[0094] S202: After a large number of repeated experimental training, the Fcp value range of each type of sound source is trained and obtained.

[0095] S203: labeling and storing the sound source type and value range to obtain the sample library,

[0096] The present invention extracts the maximum peak and spectrum features through traversing the target signal, calculates the total energy, frequency distribution mean, discrete distribution, centroid value, shape feature, energy normalization and energy distribution eigenvalue, and performs comprehensive eigenvalue matching with pre-collected multi-type sound source samples, thereby achieving efficient and accurate underwater sound source recognition and classification, thereby ensuring the reliability, accuracy and real-time response capability of the monitoring system.

[0097] Although the present invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the present invention. That is, the methods, systems and devices discussed above are examples. Various configurations may appropriately omit, replace or add various processes or components. For example, in alternative configurations, the method may be performed in an order different from that described, and / or various components may be added, omitted and / or combined. Moreover, the features described with respect to certain configurations may be combined in various other configurations, such as different aspects and elements of the configuration may be combined in a similar manner. In addition, as technology develops, the elements therein may be updated, i.e., many elements are examples and do not limit the scope of the present disclosure or claims. And it should be understood that after reading the contents of the record of the present invention, the technician may make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A passive sonar network monitoring system based on underwater drone groups, characterized in that: The passive sonar network monitoring system includes a number of drones distributed underwater, a sonar monitoring module for underwater sonar monitoring, a fixing module for adapting and fixing the sonar monitoring module to the drone, and a control station arranged above water for analyzing and processing the sound wave signals monitored by the sonar monitoring module. Among them, the drone, sonar monitoring module and control station are connected through communication technology signals. The drone includes a positioning system that is integrated with GPS, INS, acoustic positioning, visual positioning and depth sensors. Several drones are used to drop the sonar monitoring module underwater and to recover the sonar monitoring module underwater. The sonar monitoring module includes a plurality of monitoring units, each of which includes a shell with a plate-like structure, sonar sensors arranged in a matrix on the top wall of the shell, a counterweight fixed to the bottom of the shell, a positioner arranged in the shell, and a storage device for storing the monitoring data of the sonar sensor. The shell is a sealed and waterproof structure, and the interior of the shell is an airtight cavity. The fixing module includes a permanent magnet fixed in the shell, and an adsorption unit fixed on the body of the drone and used to generate an adsorption magnetic force on the permanent magnet and thereby adsorb and fix the shell.

2. The passive sonar network monitoring system according to claim 1, characterized in that: The underwater area is evenly divided into several operation areas, each of which has at least one drone and several monitoring units. The sonar sensor continuously receives sound signals from the underwater environment, and all sound signals received by the sonar sensor are recorded and stored in the memory, waiting to be further transmitted to the drone. The drone moves underwater and periodically transmits the monitoring data of all monitoring units in the same operation area in batches. The drone regularly rises to the surface to send monitoring data to the control station.

3. The passive sonar network monitoring system according to claim 2, characterized in that: The adsorption unit includes an airtight box, an electromagnetic coil installed in the box, a controller for controlling the current of the electromagnetic coil to control the electromagnetic adsorption strength of the electromagnetic coil to the permanent magnet, and a locking member for fixing the airtight box to the drone.

4. The passive sonar network monitoring system according to claim 3, characterized in that: The operation contents of placing the monitoring unit by drone include: The drone determines its current position through its own positioning system, and moves to the designated monitoring unit placement area according to the predetermined operation area division method and the instructions issued by the control station. After reaching the designated location, the drone releases the magnetic adsorption of the monitoring unit through the adsorption unit in its fixed module, allowing the monitoring unit to descend to the underwater target location through gravity. After the monitoring unit reaches the underwater target position, it performs position calibration through the internal locator to ensure that the monitoring unit is stably and accurately placed at the predetermined position, and then starts sonar monitoring.

5. The passive sonar network monitoring system according to claim 4, characterized in that: The operation of the drone to recover the underwater monitoring unit includes: The drone maintains regular contact with each monitoring unit through communication technology and receives the status data of the monitoring unit, including power supply and integrity data of the monitoring data. When the drone receives a message that a monitoring unit is short of power or the monitoring data is incomplete, it immediately records the location of the monitoring unit and notifies the control station. The UAV moves to the location of the faulty monitoring unit according to the recorded location of the work area and the instructions of the control station. The adsorption unit of the UAV is activated, and the magnetic force is generated by controlling the current of the electromagnetic coil to adsorb and fix the faulty monitoring unit to the UAV body. The UAV drives the monitoring unit to gradually float to the surface of the water, so as to bring the faulty monitoring unit back to the ground for maintenance or replacement of the power supply.

6. The passive sonar network monitoring system according to claim 5, characterized in that: The control station implements the following operating steps: S101: receiving a sound wave signal received by a drone, the sound wave signal including sound waves from different sound sources, the different sound sources including ships, marine life and natural sounds, S102: Filter the monitoring signal using a filter. S103: converting the filtered time-domain sound wave signal into a frequency-domain signal by Fourier transform, and then extracting a frequency spectrum segment within a preset frequency range [Fre1, Fre2] from the frequency-domain signal as a target signal; S104: Analyze the extracted target signals to determine the sound source type corresponding to each target signal. S105: Summarize the location information and monitoring time of the same sound source received from different sonar sensors to form comprehensive sound source information. S106: Continuously splicing the monitoring time, and further extracting and generating the movement trajectory of the sound source during the continuous monitoring time according to the position change of the sonar sensor during the continuous monitoring time.

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