A method and device for detecting variable-depth active acoustic buoys

Abstract

The present invention discloses a variable-depth active acoustic buoy detection method and device, comprising the following steps: S1. Acquiring intelligence information and remote control commands; S2. Formulating a target detection strategy and issuing control commands based on the target detection strategy; and S3. Emitting a detection signal based on the control commands. By providing external intelligence information and remote control commands to adjust the target detection strategy and optimizing the operating parameters and processes of the target detection sonar, the present invention ensures the rational and efficient implementation of the target detection strategy, enabling the timely discovery, location, and continuous tracking of underwater targets, thereby improving the accuracy of variable-depth active detection in deep or complex waters.

Description

Technical Field

[0001] The present invention relates to the field of underwater acoustic engineering, and in particular to a method and device for detecting a variable-depth active acoustic buoy. Background Art

[0002] An acoustic buoy is a device deployed in a designated sea area to acoustically detect and locate targets within a certain range. Due to the complex spatiotemporal characteristics of ocean ambient noise, it varies significantly at different times, depths, sea areas, and hydrological conditions. The detection capabilities of acoustic buoys are particularly limited when background noise is high. Furthermore, existing acoustic buoys often use passive detection for monitoring, which is incapable of measuring the range and velocity of targets, making accurate positioning difficult. The few acoustic buoys that use active detection are limited by battery power and supply issues, and cannot operate in a high power consumption state for long periods of time. Consequently, they face power shortages and short active duty cycles, making it difficult to detect, locate, and continuously track underwater targets. Furthermore, existing signal and information processing methods for buoys primarily utilize beamforming, energy detection or matched filtering, and power spectrum analysis. These methods fail to achieve integrated and autonomous active detection–location–classification–tracking (DLCT) for underwater targets under unmanned conditions, hindering timely target identification and threat assessment. Summary of the Invention

[0003] The purpose of the present invention is to provide an acoustic buoy detection method and device to autonomously complete continuous detection, positioning, classification, tracking and threat judgment of underwater targets in deep sea or complex sea areas.

[0004] To achieve the above object, the present invention provides a variable depth active acoustic buoy autonomous detection method, comprising the following steps:

[0005] S1. Obtain intelligence information and remote control commands;

[0006] S2. Formulate a target detection strategy and issue control instructions according to the target detection strategy;

[0007] S3, controlling the sonar of the acoustic buoy to send a detection signal according to the control instruction;

[0008] The steps for developing a target detection strategy include:

[0009] S201: Providing a preset detection strategy;

[0010] S202: Generate detection parameters based on the preset detection strategy, intelligence information, and remote control instructions;

[0011] S203: Performing sound field modeling according to the detection parameters and different sound propagation effects;

[0012] S204: Perform performance prediction based on the sound field modeling results, and evaluate whether the detection range and detection probability of the sonar under the current working parameters and sound propagation effect meet the preset requirements according to the performance prediction results; if so, use the detection strategy corresponding to the current detection parameters as the target detection strategy; if not, adjust the detection parameters and return to step S203.

[0013] Optionally, the intelligence information includes sea area environment intelligence and suspicious target intelligence, the sea area environment intelligence includes environmental parameters of the sea area where the acoustic buoy is located, and the suspicious target intelligence includes one or more of suspicious target location, suspicious target type, and suspicious target threat level.

[0014] Optionally, the intelligence information also includes: status information of the acoustic buoy, and the status information of the acoustic buoy includes one or more of the position, posture and drifting speed of the acoustic buoy.

[0015] Optionally, the sound propagation effect includes one or more of a direct sound path, a deep-sea sound channel, a first convergence zone, a reliable sound path, and a seabed reflection;

[0016] The performance prediction includes one or more of propagation loss, reverberation level, sonar range, sonar detection probability, seabed clutter intensity and bright spot structure, target intensity and bright spot structure.

[0017] Optionally, the detection parameters include a transmission signal waveform, a signal transmission control instruction and a depth change instruction.

[0018] Optionally, the target detection strategy also includes providing a target echo and background interference feature forecast, wherein the target echo and background interference feature forecast includes a time-space-frequency basic feature forecast of the target echo and one or more background interferences such as noise, reverberation, and seabed clutter in the current sonar working mode.

[0019] Optionally, after step S3, the following steps are further included:

[0020] S4: receiving an echo signal and performing signal processing on the echo signal;

[0021] S5: generating a detection image according to the output of the signal processing;

[0022] S6: Process the detection images accumulated over multiple pings to form target traces, and then automatically identify and evaluate the target attributes and threat level to generate target detection results;

[0023] S7: Send the target detection result to an external terminal.

[0024] Optionally, performing signal processing on the echo signal includes:

[0025] S401: extracting effective acquisition signals from the received echo signal data according to the data transmission protocol, and regularizing the dynamic range and time-space sequence to form multi-channel array element-level signal data;

[0026] S402: Filtering and homogenizing the multi-channel element-level signal data, including bandpass filtering, scaling filtering, pre-homogenization, and constant low-sidelobe spatial filtering; and splitting the multi-channel element-level signal data into two left and right sub-array beams for output;

[0027] S403: Calculate the local reverberation Doppler shift and spread in the specified beam direction and suppress it according to the drift direction and speed of the acoustic buoy and the transmission signal parameters;

[0028] S404: Based on the transmitted waveform and the predicted target echo characteristics, a series of signal replicas of multiple wavelet and multi-velocity channels are generated for each of the two sub-array beams, and then matched filtering is performed on each replica;

[0029] S405: The multi-velocity matching output of any wavelet corresponds to an ambiguity map, and the multiple ambiguity maps output by the multiple wavelets of any sub-array beam are nonlinearly fused to obtain super-resolution capability in the joint time-frequency domain;

[0030] S406: After matching and fusing the left and right sub-array beams in the specified direction, the beam is output as a total array beam, and the total array beam is subjected to phase unitization processing to suppress mainlobe interference and obtain super-resolution capability in the joint space-time domain;

[0031] S407: Based on the target echo feature prediction and the influence of the time-space-frequency super-resolution processing, a post-homogenization process is performed on the total array beam to adapt to the statistical characteristics of the super-resolution echo.

[0032] Optionally, step S5 includes:

[0033] S501: In the natural coordinate system of the acoustic buoy, the post-homogenized output data is accumulated and smoothed or resampled into a planar image according to the effective display area as a relative detection image, and the relative detection image is completely refreshed once for each detection ping;

[0034] S502: performing coordinate conversion according to the position, receiving array direction, and receiving array attitude information of the acoustic buoy;

[0035] S503: Using the plane image of the relative detection image after coordinate conversion as the absolute detection image;

[0036] Step S6 includes:

[0037] S601: Calculate the constant false alarm threshold, target speed limit, and target scale limit based on the target echo and background interference feature prediction to form a multi-feature integrated threshold, automatically detect the data on the absolute detection screen, retain the data that exceeds the threshold, and zero out the remaining data;

[0038] S602: Target point extraction and contact-level tracking are performed on the automatically detected image data;

[0039] S603: Based on the contact-level tracking results accumulated over multiple pings, a target track is formed. The target track is then checked for consistency with the motion pattern of the underwater target. The track data is corrected based on the result of the check and the corrected data is returned to step S601 to recalculate the multi-feature integrated threshold and repeat steps S602 and S603.

[0040] S604: Based on the accumulated automatic detection and tracking results, the target attributes and threat level are automatically identified and evaluated to form a DLCT result, thereby completing the autonomous detection.

[0041] The present invention also provides an acoustic buoy device, which is equipped with a variable depth active sonar system and uses the variable depth active acoustic buoy detection method as described in any one of the above items to perform target detection.

[0042] The beneficial effects of the present invention are as follows: by formulating target detection strategies through externally provided intelligence information and remote control commands, it is possible to ensure safe and efficient interaction between the acoustic buoy device and the user, and to meet the control and detection strategy implementation requirements of the various components within the acoustic buoy device. By optimizing the working parameters and processes of the target detection sonar, it is possible to ensure the reasonable and efficient implementation of the automatic detection strategy, and to produce target echo and background interference feature forecasts for signal processing. By adaptively processing the signal data based on the target echo and background interference features, the signal processing capability and efficiency are effectively improved. The system has good recognition capabilities and can adapt to and meet the variable depth active detection accuracy requirements in deep sea or sea areas with complex topography. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 1 is a schematic diagram of the component structure and deployment configuration of an acoustic buoy device according to one embodiment of the present invention;

[0044] Figure 2 is a flow chart of a variable depth active acoustic buoy detection method according to one embodiment of the present invention;

[0045] Figure 3 is a flow chart of a target detection strategy for variable depth active acoustic buoy detection according to one embodiment of the present invention;

[0046] Figure 42 is a schematic diagram of a target detection strategy generation framework for variable depth active acoustic buoy detection according to an embodiment of the present invention;

[0047] Figure 5 is an information processing flow chart of variable depth active acoustic buoy detection according to one embodiment of the present invention;

[0048] Figure 6 is a flow chart of a signal processing method for variable depth active acoustic buoy detection according to one embodiment of the present invention;

[0049] Figure 7 This is a flow chart of generating a detection screen using an echo signal from a variable depth active acoustic buoy according to one embodiment of the present invention;

[0050] Figure 8 1 is a schematic diagram of a process for detecting a variable-depth active acoustic buoy according to an embodiment of the present invention.

[0051] Description of main reference numerals:

[0052] 1. Floating bladder; 2. Surface tank; 3. Generator; 4. Communication module; 5. Top electronic unit; 6. Starting battery; 7. Charger; 8. Intake pipe; 9. Exhaust pipe; 10. Fuel tank; 11. Fuel bag; 12. Cable car cabin; 13. Winch; 14. Bottom cabin; 15. Power amplifier; 16. Battery pack; 17. Transmitting array; 18. Receiving array; 19. Bottom electronic unit; 20. Array element; 21. Center pole; 22. Receiving arm; 23. Sinking block. DETAILED DESCRIPTION

[0053] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0054] Unless expressly stated otherwise, throughout the specification and claims, the term "comprise" or variations such as "include" or "comprising", etc., will be understood to include the stated elements or components but not to exclude other elements or other components.

[0055] In the description of the present invention, the terms "first" ("firstly"), "second" ("secondly"), etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, a feature specified as "first" ("firstly") or "second" ("secondly") may explicitly or implicitly include at least one of the features. In addition, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0056] In the description of the present invention, reference to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the described embodiment may be combined with other embodiments.

[0057] Reference Figure 1 In a preferred embodiment of the present invention, the acoustic buoy device is a medium-to-large surface buoy with a sound source capable of long-term transmission and a base array capable of varying depth over a wide range. The buoy comprises a float bladder 1 and a buoy body. The buoy body includes an active depth-variable sonar system. The buoy body can be divided into four compartments, from top to bottom: a surface compartment 2, a fuel tank 10, a cable car compartment 12, and a bottom compartment 14. The surface compartment 2 houses a generator 3, a charger 7, a starting battery 6, a communication module 4, and a top-level electronics unit 5. The float bladder 1 is positioned outside the surface compartment 2. The fuel tank 10 houses a fuel pack 11 that supplies fuel to the generator 3. The cable car compartment 12 houses a winch 13 and a load-bearing cable. The bottom compartment 14 contains a power amplifier 15 and a battery pack 16. The buoy also includes a transmitting array 17, a receiving array 18, and a bottom-level electronics unit 19, all connected to the end of the load-bearing cable.

[0058] The fuel in the fuel tank 10 is supplied to the generator 3, which generates electricity to charge the battery pack 16 and then provides energy for the power unit of the acoustic buoy, enabling long-term active detection in deep sea areas.

[0059] In some embodiments, as Figure 2 As shown, the present invention provides a variable depth active acoustic buoy detection method, comprising the following steps:

[0060] S1. Obtain intelligence information and remote control commands;

[0061] S2. Formulate a target detection strategy and issue control instructions according to the target detection strategy;

[0062] S3. Control the sonar of the acoustic buoy to send a detection signal according to the control instruction.

[0063] In step S1 , the acoustic buoy communicates with an external terminal through the communication module 4 . The external terminal may be a user or a shore control center, and the communication module 4 may be a satellite or a wireless communication component.

[0064] In some embodiments, the intelligence information includes sea area environmental intelligence and suspicious target intelligence. The sea area environmental intelligence includes environmental parameters of the sea area where the acoustic buoy is located, such as water depth, underwater topography, and wind and wave parameters. The suspicious target intelligence includes one or more of the following: suspicious target location, suspicious target type, and suspicious target threat level. The remote control command information includes acoustic buoy commands such as power on, power off, depth change (changing the depth of the transmitting array 17 and the receiving array 18), transmission change (changing the transmission signal type / frequency band / bandwidth / pulse width, transmission interval, transmission power, transmission direction, etc.), start transmission, stop transmission, release the battery pack 16, and self-destruct, which are used to control the acoustic buoy's transmission signal, posture, and operating status.

[0065] In some embodiments, the intelligence information also includes: acoustic buoy status information, including one or more of the following: the acoustic buoy's geographic location, the receiving array 18's attitude, and the drift velocity. The acoustic buoy status information is provided by an external positioning system, such as a satellite or base station, as positioning calibration data. This information is used by the positioning module, which calculates the acoustic buoy's position and drift velocity based on the positioning calibration data and transmits it to the top electronic unit 5 and the bottom electronic unit 19.

[0066] The detection signal transmission is controlled by the top-level electronic unit 5 sending a control signal to the power amplifier 15, generating a multi-channel transmit signal. The multi-channel transmit signal is amplified by the power amplifier 15 to a customized power level and then sent to the transmit array 17. The transmit array 17 performs electro-acoustic conversion and radiates the acoustic signal into the water using a specified vertical beam steering (horizontal omnidirectional without beam steering). The multi-channel transmit signal is derived from a single-channel basic transmit waveform. The number of channels is equal to the number of elements in the transmit array 17. The time delay difference between each channel is determined based on the vertical beam steering calculation.

[0067] Further, refer to Figure 3 The top electronic unit 5 in the acoustic buoy formulates a target detection strategy based on the acquired intelligence information, remote control instructions, and status information, which specifically includes the following steps:

[0068] S201: Providing a preset detection strategy. The preset detection strategy is preset in advance in the memory of the top electronic unit 5 of the acoustic buoy.

[0069] S202: Generate detection parameters based on the preset detection strategy, intelligence information, and remote control instructions. The detection parameters mainly include: transmission signal waveform, signal transmission control instructions, and depth change instructions;

[0070] S203: Performing sound field modeling based on the detection parameters and different sound propagation effects,

[0071] S204: Perform performance prediction based on the sound field modeling results, and evaluate whether the detection range and detection probability of the sonar under the current working parameters and sound propagation effect meet the preset requirements according to the performance prediction results; if so, use the detection strategy corresponding to the current detection parameters as the target detection strategy; if not, adjust the detection parameters and return to step S203.

[0072] Here, steps S203-S204 are an automatic optimization step of a target detection strategy. Figure 4 , specifically divided into three parts:

[0073] T1. Strategy Generation. Target detection strategies include variable transmit and depth. Determining the optimal strategy essentially involves optimizing the sonar transmit and depth-related operating parameter settings and process control. Therefore, the sonar operating parameter optimization component is the core component of target detection strategy generation. This component's inputs include preset parameter settings derived from pre-set detection strategies, remote control parameter settings obtained through user remote control commands, and parameter adjustments during sonar performance review. Its temporary output includes a series of transmit and depth parameters, including transmit depth, receive depth, transmit pointing and beam steering, receive pointing and beam steering, transmit power or source level, transmit signal type, transmit frequency band and bandwidth, and transmit pulse width and interval. These temporary outputs serve as device condition inputs for the acoustic field modeling component. These optimized parameters serve as the final output of this component and enter the target detection strategy generation component. Combined with the timing process, they form the final target detection strategy, including transmit waveform, transmit control commands, and depth-variation commands.

[0074] T2. Acoustic Field Modeling. This section's core component is the modeling of diverse acoustic propagation effects, a key feature of the acoustic buoy. Based on the input transmission, array depth, environment, and target conditions, it selects one or more of a variety of acoustic propagation effects, including direct acoustic path, deep-sea acoustic channel, first convergence zone, reliable acoustic path, and seabed reflection, to model the underwater acoustic field. This includes modeling of surface scattering, seabed scattering, target scattering, and ambient noise. Input parameters fall into three categories: 1. The transmit signal, transmit / receive array depth, and transmit / receive pointing parameters temporarily output by the sonar operating parameter optimization component in T1; 2. Ocean environmental intelligence, either pre-set or remotely transmitted, including surface parameters (sea state, wave height, surface scattering coefficient, etc.), seabed parameters (bottom type, stratification, seabed scattering coefficient), sea depth, seabed topography, sound velocity profile, mesoscale flow parameters, and background noise level; and 3. Marine target intelligence, either pre-set or remotely transmitted, including the type, location, size, and velocity of large surface targets and suspicious underwater targets. The sound field modeling result is the final output of the component and will enter the performance prediction part.

[0075] T3. Performance Prediction. Based on acoustic field modeling, a series of calculations are performed, including propagation loss prediction, reverberation level prediction, sonar range prediction, sonar detection probability estimation, seafloor clutter intensity and bright spot structure prediction, and target intensity and bright spot structure prediction. This evaluates the sonar's detection range and detection probability under the current operating parameters and sound propagation path to determine whether the sonar is achieving optimal performance and possible parameter setting improvements. This feedback is fed back to the sonar operating parameter optimization component in T1, starting a new cycle of "parameter setting → acoustic field modeling → performance prediction." This cycle is repeated until a parameter setting solution that meets performance requirements is obtained.

[0076] In addition, in some embodiments, the mathematical model and detection parameters established by the target detection strategy optimization link can also provide a prediction of the target echo and background interference characteristics. The so-called target echo and background interference characteristic prediction refers to the modeling and prediction of the target echo and background interference characteristics: based on the calculation of various parameters in the sound field modeling and sonar performance prediction, a physical or numerical description of the time, space and frequency characteristics of the target echo, reverberation and seabed clutter and other signals under the current sonar working mode that is adapted to the target and environmental intelligence is given. In theory, under the optimized sonar working parameters, target detection is carried out according to the strategy, and the target echo and background interference in the received signal should have characteristics consistent with the prediction. Therefore, this characteristic prediction is an important basis for the subsequent implementation of signal processing adapted to the environment and target characteristics.

[0077] The echo signal refers to the multi-channel element-level signal that is received by the receiving array 18 after the transmitted detection wave is reflected by the target or obstacle, and is converted by the receiving array 18 into an acoustic-to-electrical signal and sent to the bottom electronic unit 19. Subsequent signal processing is to perform data processing on the multi-channel element-level signal, such as Figure 5 shown.

[0078] In some embodiments, step S3 may be followed by an echo signal processing step, specifically comprising:

[0079] S4: Receive the echo signal and perform signal processing on the echo signal.

[0080] S5: Generate a detection picture according to the output of the signal processing.

[0081] S6: Process the detection images accumulated over multiple pings to form target traces, and then automatically identify and evaluate the target attributes and threat level to generate target detection results.

[0082] S7: Send the target detection result to an external terminal.

[0083] Further references Figure 6 In some embodiments, the step of performing signal processing on the echo signal includes:

[0084] S401: extracting effective acquisition signals from the received echo signal data according to the data transmission protocol, and regularizing the dynamic range and time-space sequence to form multi-channel array element-level signal data.

[0085] S402: Filtering and homogenizing the multi-channel array element-level signal data; including:

[0086] Bandpass filtering and scale filtering. The current transmission frequency band and bandwidth are extracted according to the transmission control command, and the range resolution element and maximum resolution scale are calculated. Based on this, the bandpass filtering and scale filtering ranges are set to filter the input data.

[0087] Pre-homogenization: Implement homogenization processing based on the reverberation and clutter characteristics to reduce the non-stationary, non-Gaussian, and non-white characteristics of the data and reduce its dynamic range.

[0088] Constant low sidelobe spatial filtering: Based on the array expansion state, constant low sidelobe spatial filtering is implemented to reduce sidelobe interference and split the beam into two left and right sub-array outputs.

[0089] S403: Calculate the local reverberation Doppler shift and spread in the specified beam direction according to the drift direction and speed of the acoustic buoy and the transmission signal parameters, and suppress them; preferably, use a nulling filter for suppression.

[0090] S404: Based on the transmitted waveform and predicted target echo characteristics, a series of multi-wavelet, multi-velocity channel signal replicas are generated for each of the two sub-array beams. Matched filtering is then performed on each replica. The multi-wavelet here includes both the combined wavelet of the combined signal and the bright spot wavelet of the multi-bright spot echo.

[0091] S405: The multi-velocity matching output of any wavelet corresponds to an ambiguity map, and the multiple ambiguity maps output by the multi-wavelet of any sub-array beam are nonlinearly fused to obtain super-resolution capability in the joint time-frequency domain.

[0092] S406: After matching and fusing the left and right sub-array beams in the specified direction, a total array beam is output, and phase unitization is performed on the total array beam to suppress mainlobe interference and obtain super-resolution capability in the joint space-time domain.

[0093] S407: Based on the target echo feature prediction and the influence of the time-space-frequency super-resolution processing, a post-homogenization process is performed on the total array beam that is adapted to the statistical features of the super-resolution echo, which can further reduce false alarms.

[0094] Further references Figure 7 In some embodiments, step S5 includes:

[0095] S501: Relative detection image generation. In the acoustic buoy's natural coordinate system, the post-homogenized output data is accumulated, smoothed, or resampled to a planar image based on the effective display area, creating the relative detection image. This relative detection image is fully refreshed once per detection ping. The acoustic buoy's receiving array 18 natural coordinate system is defined by relative azimuth or beam angle, range, relative radial velocity, and data intensity or amplitude.

[0096] S502: Coordinate transformation is performed based on the acoustic buoy's position, receiving array orientation, and receiving array attitude information. A disadvantage of the relative coordinate system is that it takes into account motion factors such as the drift of the buoy, the rotation and tilt of the receiving array 18 or the transmitting array 17, and so on, making it impossible to determine the target's true motion state. By designing and implementing coordinate transformation based on the acoustic buoy's position, array orientation, and array attitude information, the target state can be further calibrated, improving detection accuracy.

[0097] S503: The coordinate-converted planar image of the relative detection image is used as the absolute detection image. This coordinate conversion transforms points on the relative detection image into points in a coordinate system consisting of geographic location (longitude-latitude, or horizontal and vertical displacement relative to a fixed geographic point)-absolute radial velocity-intensity. This planar image, designed based on ergonomics, represents the absolute detection image. The points on this image have been freed from motion effects.

[0098] In some embodiments, step S6 includes:

[0099] S601: Calculate the constant false alarm threshold, target speed limit, and target scale limit based on the target echo and background interference feature prediction to form a multi-feature comprehensive threshold, automatically detect the data on the absolute detection screen, retain the data that exceeds the threshold, and zero the remaining data.

[0100] S602: Target point extraction and contact-level tracking are performed on the automatically detected image data. The weights of position and velocity information can be dynamically adjusted during the tracking process.

[0101] S603: Based on the contact-level tracking results accumulated over multiple pings, a target track is generated. The track data is then corrected based on the consistency of the target track with the underwater target's motion patterns. This correction is then returned to step S601 to recalculate the multi-feature integrated threshold and repeat steps S602 and S603. Track data correction involves determining target attributes based on the consistency of the track data with the underwater target's motion patterns. Alternatively, track data that was lost or erroneously tracked is restored or reassigned based on the motion patterns. Disrupted track data are discarded, while the patterns formed by stable track data are fed back to step S601 to modify the velocity or scale integrated thresholds, resulting in new, lower false alarm automatic detection.

[0102] S604: Based on the accumulated automatic detection and tracking results, the target attributes and threat level are automatically identified and evaluated to form a DLCT result, completing the autonomous detection. The DLCT result includes the target's position, speed, size, type, and threat level.

[0103] On the other hand, an embodiment of the present invention also provides an acoustic buoy device, which carries a variable depth active sonar system. The variable depth active sonar system can radiate acoustic pulse signals into the water at different depths with high power and receive its echo signals with a large aperture and process them autonomously, and use the variable depth active acoustic buoy detection method as described in any of the above items to perform target detection.

[0104] In a preferred embodiment of the present invention, the bottom electronic unit 19 sends the target detection results to the top electronic unit 5 for aggregation and then sends them to the user via satellite or wireless communication components.

[0105] like Figure 8 As shown, in a preferred embodiment of the present invention, the information sent to the user may also include: the PING time corresponding to the target position detection result, and the real-time monitoring information and alarm information of the status of the acoustic buoy device, wherein the real-time monitoring information includes: the depth of the receiving array 18 and the transmitting array 17, the temperature and remaining power of the battery pack 16, the remaining fuel, the status of the generator 3, the status of the charger 7, the status of the winch 13, the cable length, the position of the acoustic buoy, the remaining battery power of the top unit, the remaining battery power of the bottom unit, etc. The alarm information includes: component failure alarm, collision alarm, acoustic array bottoming alarm, high-threat target alarm, etc.

[0106] In this embodiment of the present invention, the top-level electronic unit 5 is responsible for collecting and aggregating the above information, and transmitting it to the user via the communication module. Real-time status monitoring information and alarm information are generated from various components. Target detection results include target location (such as direction, distance, and latitude and longitude), speed, type, and threat level. Real-time monitoring information supports users in remotely assessing the operating status of the buoy. Alarm information alerts users to abnormal or dangerous conditions. Alarm information is generated in real time and is sent to the top-level electronic unit 5 as soon as it is generated, then transmitted to the user via satellite or wireless communication components. The acoustic buoy's location information is generated from satellite or wireless communication components and transmitted to the user independently at a specific refresh rate, or sent to the user together with real-time status monitoring information.

[0107] In other embodiments of the present invention, the underlying electronic unit 19 can be configured with a signal recorder to completely or selectively record the array element-level receiving signals, as well as array direction, array depth, array attitude, transmission signal, PING time, mark position, target echo and background interference feature forecast and other information for users to perform offline analysis after the acoustic buoy data is recovered.

[0108] In a preferred embodiment of the present invention, the user can remotely change the target detection strategy by sending new remote control instructions and intelligence information, thereby realizing remote intervention in the target detection process. The top-level electronic unit 5 is provided with a target detection strategy generation module, and the preset detection strategy is the initial value of the target detection strategy generation module. The array depth requirements and the requirements for the transmitted signal waveform, interval, power, etc. sent by the user will be used as new working parameter optimization inputs, and the target or environmental intelligence sent by the user will become the conditional input for the new sound field modeling, thereby affecting the generation of the new target detection strategy. After the preset detection strategy, remote control instructions and intelligence information jointly support the generation of the new target detection strategy, the new control instructions and parameters for each relevant component will be sent and executed immediately, and the target echo and background interference feature forecast information will also be sent to the bottom-level electronic unit 19 in a timely manner after being updated to process the target detection signal.

[0109] It should be noted that the acoustic buoy component compartment structure and deployment form, information and signal flow, target detection strategy generation framework, received signal processing method framework, etc. shown in the accompanying drawings are merely corresponding schematic diagrams or examples of their respective embodiments, which are only for the purpose of more clearly illustrating the technical solution of the present invention and do not constitute a limitation on the content of the present invention and its technical solution. It is known to those skilled in the art that with the evolution of acoustic buoy devices and the expansion of application scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0110] The foregoing descriptions of specific exemplary embodiments of the present invention are for purposes of illustration and description. These descriptions are not intended to limit the invention to the precise forms disclosed, and it is apparent that many variations and modifications are possible in light of the foregoing teachings. The exemplary embodiments have been selected and described for the purpose of explaining the specific principles of the invention and their practical application, thereby enabling those skilled in the art to realize and utilize a variety of exemplary embodiments of the invention and various options and modifications. The scope of the invention is intended to be defined by the claims and their equivalents.

Claims

1. A variable depth active acoustic buoy detection method, characterized in that: The following steps are involved: S1. Obtain intelligence information and remote control commands; S2. Formulate a target detection strategy and issue control instructions according to the target detection strategy; S3, controlling the sonar of the acoustic buoy to send a detection signal according to the control instruction; The steps for developing a target detection strategy include: S201: Providing a preset detection strategy; S202: Generate detection parameters based on the preset detection strategy, intelligence information, and remote control instructions; S203: Performing sound field modeling according to the detection parameters and different sound propagation effects; S204: Performing a performance prediction based on the acoustic field modeling results, and evaluating whether the detection range and detection probability of the sonar under the current operating parameters and sound propagation effects meet preset requirements based on the performance prediction results; if so, using the detection strategy corresponding to the current detection parameters as the target detection strategy; if not, adjusting the detection parameters and returning to step S203; After step S3, the following steps are also included: S4: receiving an echo signal and performing signal processing on the echo signal; S5: generating a detection image according to the output of the signal processing; S6: Process the detection images accumulated over multiple pings to form target traces, and then automatically identify and evaluate the target attributes and threat level to generate target detection results; S7: Sending the target detection result to an external terminal; The signal processing includes: S401: extracting effective acquisition signals from the received echo signal data according to the data transmission protocol, and regularizing the dynamic range and time-space sequence to form multi-channel array element-level signal data; S402: Filtering and homogenizing the multi-channel element-level signal data, including bandpass filtering, scaling filtering, pre-homogenization, and constant low-sidelobe spatial filtering; and splitting the multi-channel element-level signal data into two left and right sub-array beams for output; S403: Calculate the local reverberation Doppler shift and spread in the specified beam direction and suppress it according to the drift direction and speed of the acoustic buoy and the transmission signal parameters; S404: Based on the transmitted waveform and the predicted target echo characteristics, a series of signal replicas of multiple wavelet and multi-velocity channels are generated for each of the two sub-array beams, and then matched filtering is performed on each replica; S405: The multi-velocity matching output of any wavelet corresponds to an ambiguity map, and the multiple ambiguity maps output by the multiple wavelets of any sub-array beam are nonlinearly fused to obtain super-resolution capability in the joint time-frequency domain; S406: After matching and fusing the left and right sub-array beams in the specified direction, the beam is output as a total array beam, and the total array beam is subjected to phase unitization processing to suppress mainlobe interference and obtain super-resolution capability in the joint space-time domain; S407: Based on the target echo feature prediction and the influence of the time-space-frequency super-resolution processing, a post-homogenization process is performed on the total array beam to adapt to the statistical characteristics of the super-resolution echo.

2. The variable depth active acoustic buoy detection method according to claim 1, characterized in that: The intelligence information includes sea area environment intelligence and suspicious target intelligence. The sea area environment intelligence includes environmental parameters of the sea area where the acoustic buoy is located, and the suspicious target intelligence includes one or more of the suspicious target location, suspicious target type, and suspicious target threat level.

3. The variable depth active acoustic buoy detection method according to claim 2, characterized in that: The intelligence information also includes: status information of the acoustic buoy, and the status information of the acoustic buoy includes one or more of the position, posture and drifting speed of the acoustic buoy.

4. The variable depth active acoustic buoy detection method according to claim 1, characterized in that: The sound propagation effect includes one or more of a direct sound path, a deep-sea sound channel, a first convergence zone, a reliable sound path, and a seabed reflection; The performance prediction includes one or more of propagation loss, reverberation level, sonar range, sonar detection probability, seabed clutter intensity and bright spot structure, target intensity and bright spot structure.

5. The variable depth active acoustic buoy detection method according to claim 1, characterized in that: The detection parameters include the emission signal waveform, signal transmission control instructions and depth change instructions.

6. The variable depth active acoustic buoy detection method according to claim 5, characterized in that: The target detection strategy also includes providing a target echo and background interference feature forecast, which includes a prediction of the basic time-space-frequency characteristics of the target echo and one or more background interferences such as noise, reverberation, and seabed clutter in the current sonar working mode.

7. The variable depth active acoustic buoy detection method according to claim 1, characterized in that: Step S5 includes: S501: In the natural coordinate system of the acoustic buoy, the post-homogenized output data is accumulated and smoothed or resampled into a planar image according to the effective display area as a relative detection image, and the relative detection image is completely refreshed once for each detection ping; S502: performing coordinate conversion according to the position, receiving array direction, and receiving array attitude information of the acoustic buoy; S503: Using the plane image of the relative detection image after coordinate conversion as the absolute detection image; Step S6 includes: S601: Calculate the constant false alarm threshold, target speed limit, and target scale limit based on the target echo and background interference feature prediction to form a multi-feature integrated threshold, automatically detect the data on the absolute detection screen, retain the data that exceeds the threshold, and zero out the remaining data; S602: Target point extraction and contact-level tracking are performed on the automatically detected image data; S603: Based on the contact-level tracking results accumulated over multiple pings, a target track is formed. The target track is then checked for consistency with the motion pattern of the underwater target. The track data is corrected based on the result of the check and the corrected data is returned to step S601 to recalculate the multi-feature integrated threshold and repeat steps S602 and S603. S604: Based on the accumulated automatic detection and tracking results, the target attributes and threat level are automatically identified and evaluated to form a DLCT result, thereby completing the autonomous detection.

8. An acoustic buoy device, characterized in that: The acoustic buoy device is loaded with a variable depth active sonar system, and uses the variable depth active acoustic buoy detection method according to any one of claims 1 to 7 to perform target detection.

Images