CN115184940A - Depth-variable active acoustic buoy detection method and device - Google Patents

Abstract

The invention discloses a method and a device for detecting a variable-depth active acoustic buoy, which comprise the following steps: s1, acquiring information and a remote control instruction; s2, making a target detection strategy and sending a control command according to the target detection strategy; and S3, sending a detection signal according to the control instruction. The invention adjusts the target detection strategy by providing external information and remote control instructions, optimizes the working parameters and flow of the target detection sonar, ensures the reasonable and efficient implementation of the target detection strategy, finds and positions underwater targets in time and continuously tracks the underwater targets, and improves the variable-depth active detection precision of deep sea or complex sea areas.

Description

Variable-depth active acoustic buoy detection method and device

Technical Field

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

Background

An acoustic buoy is a device which is arranged in a designated sea area and used for carrying out acoustic detection and positioning on a target in a certain range around the device. Because the time-space domain characteristics of the marine environmental noise are very complex, the marine environmental noise in different time, different depths, different sea areas and different hydrology has great difference, and particularly when the background noise is high, the detection capability of the acoustic buoy is very limited. In addition, in the prior art, the acoustic buoys are often monitored in a passive detection mode, so that distance measurement and speed measurement cannot be performed on a target, accurate positioning is difficult, and a few acoustic buoys adopting active detection are limited by the problems of battery energy carrying and supply and cannot be in a high-power consumption state for a long time, so that the underwater target cannot be found and positioned and continuously tracked in time due to the limitation of insufficient power and short effective guard; in addition, the existing signal and information processing method of the buoy device mainly performs processing such as beam forming, energy Detection or matched filtering, power spectrum analysis and the like, and cannot achieve integration and autonomy of active Detection-positioning-Classification-Tracking (DLCT) aiming at an underwater target under an unmanned condition, so that timely identification and threat judgment of the target are influenced.

Disclosure of Invention

The invention aims to provide an acoustic buoy detection method and device to autonomously complete continuous detection, positioning, classification, tracking and threat judgment of an underwater target in deep sea or complex sea areas.

In order to achieve the purpose, the invention provides a variable-depth active acoustic buoy autonomous detection method, which comprises the following steps of:

s1, acquiring information and a remote control instruction;

s2, making a target detection strategy and sending a control command according to the target detection strategy;

s3, controlling a sonar of the acoustic buoy to send out a detection signal according to the control instruction;

the step of formulating the target detection strategy comprises the following steps:

s201: providing a preset detection strategy;

s202: generating detection parameters according to a preset detection strategy, information and a remote control instruction;

s203: performing sound field modeling according to the detection parameters and different sound propagation effects;

s204: performing performance forecasting based on the sound field modeling result, and evaluating whether the detection range and the detection probability of the sonar under the current working parameters and the sound propagation effect meet the preset requirements or not according to the performance forecasting result; if so, taking the detection strategy corresponding to the current detection parameter as a target detection strategy; if not, adjusting the detection parameters, and returning to step S203.

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

Optionally, the intelligence information further includes: acoustic buoy state information including one or more of an acoustic buoy position, attitude, and drift velocity.

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 sea floor reflection;

the performance forecast comprises one or more of propagation loss, reverberation level, sonar working distance, sonar detection probability, seabed clutter intensity and bright spot structure, target intensity and bright spot structure.

Optionally, the detection parameters include a transmission signal waveform, a signal transmission control instruction, and a deepening instruction.

Optionally, the target detection strategy further includes providing a target echo and background interference feature forecast, where the target echo and background interference feature forecast includes a space-time-frequency basic feature forecast of one or more background interferences of a target echo and noise, reverberation, and a sea bottom clutter in a current sonar working mode.

Optionally, after step S3, the method further includes:

s4: receiving an echo signal and carrying out signal processing on the echo signal;

s5: generating a detection picture according to the output of the signal processing;

s6: processing the detection pictures accumulated by the PINGs to form a target point trace, and further automatically identifying and evaluating target attributes and threat levels to generate a target detection result;

s7: and sending the target detection result to an external terminal.

Optionally, the signal processing the echo signal includes:

s401: extracting effective acquisition signals from received echo signal data according to a data transmission protocol, and carrying out normalization on a dynamic range and a time-space sequence to form multi-channel array element level signal data;

s402: filtering and homogenizing multi-channel array element level signal data; the method comprises the steps of band-pass filtering, scale filtering, prepositive homogenization and constant low sidelobe spatial filtering; splitting multi-channel array element level signal data into a left sub-array beam and a right sub-array beam for output;

s403: calculating and suppressing the Doppler frequency shift and the expansion of local reverberation in the appointed wave beam direction according to the drifting direction and speed of the acoustic buoy and the parameters of a transmitting signal;

s404: respectively generating a series of signal copies of a multi-wavelet multi-speed channel for two subarray wave beams according to the transmitted waveform and target echo characteristic forecast, and then carrying out matched filtering on the copies one by one;

s405: the multi-speed matching output of any wavelet corresponds to a ambiguity map, and the multiple ambiguity maps output by the multiple wavelets of any subarray wave beam are subjected to nonlinear fusion to obtain the super-resolution capability on a time-frequency joint domain;

s406: based on the fact that a left sub-array beam and a right sub-array beam in the designated direction are matched and fused to serve as a main array beam to be output, phase unitization processing is conducted on the main array beam to inhibit main lobe interference and obtain super-resolution capability on a space-time joint domain;

s407: and performing post-homogenization treatment adaptive to the echo statistical characteristics after super-resolution on the total array beam according to the target echo characteristic prediction and the influence of time-space-frequency super-resolution treatment.

Optionally, step S5 includes:

s501: accumulating, smoothing or resampling the post-homogenized output data into a plane image as a relative detection picture according to the effective display area under a natural coordinate system of the acoustic buoy, and completely refreshing each detection PING of the relative detection picture once;

s502: performing coordinate conversion according to the position information, the receiving array direction information and the receiving array attitude information of the acoustic buoy;

s503: taking the plane image of the relative detection picture after coordinate conversion as an absolute detection picture;

step S6 comprises:

s601: calculating a constant false alarm threshold, a target speed limit and a target scale limit according to target echo and background interference characteristic forecast, forming a multi-characteristic comprehensive threshold, automatically detecting data on an absolute detection picture, reserving data passing the threshold, and nulling the rest data;

s602: performing target point extraction and contact level tracking on the automatically detected picture data;

s603: forming a target point trace according to a contact level tracking result accumulated by the PINGs, performing consistency judgment on the target point trace and an underwater target motion rule, correcting trace data according to a judgment result, returning the corrected data to the step S601, recalculating the multi-feature comprehensive threshold, and repeating the steps S602 and S603;

s604: and according to the accumulation of the automatic detection and tracking results, automatically identifying and evaluating the target attribute and the threat level to form a DLCT result and finish autonomous detection.

The invention also provides an acoustic buoy device, which is a load-deepening active sonar system and adopts the deepening active acoustic buoy detection method to detect the target.

The invention has the beneficial effects that: the target detection strategy is formulated through information and remote control instructions provided by the outside, so that safe and efficient interaction between the acoustic buoy device and a user can be ensured, the control and detection strategy implementation requirements of each component in the acoustic buoy device can be met, reasonable and efficient automatic detection strategy implementation can be ensured through optimizing the working parameters and the flow of the target detection sonar, target echo and background interference characteristic forecast for signal processing can be produced, signal data are processed adaptively through the target echo and the background interference characteristic, the capacity and the efficiency of signal processing are effectively improved, a good identification function is realized, and the requirements of variable-depth active detection precision of deep sea or a landform complex sea area can be adapted and met.

Drawings

FIG. 1 is a schematic diagram of the components of an acoustic buoy device according to one embodiment of the present invention in a deployed configuration;

FIG. 2 is a flow chart of a method for variable depth active acoustic buoy detection according to an embodiment of the present invention;

FIG. 3 is a flow diagram of an object detection strategy for variable depth active acoustic buoy detection in accordance with an embodiment of the present invention;

FIG. 4 is a block diagram of an object detection strategy generation framework for variable depth active acoustic buoy detection in accordance with an embodiment of the present invention;

FIG. 5 is an information processing flow diagram for variable depth active acoustic buoy detection according to an embodiment of the present invention;

FIG. 6 is a flow chart of a signal processing method for variable depth active acoustic buoy detection according to an embodiment of the present invention;

FIG. 7 is a flow chart of an echo signal generation detection screen detected by the variable depth active acoustic buoy according to an embodiment of the present invention;

fig. 8 is a process diagram of a variable depth active acoustic buoy detection method according to an embodiment of the invention.

Description of the main reference numerals:

1. a floating bag; 2. a water surface cabin; 3. a generator; 4. a communication module; 5. a top layer electronic unit; 6. starting the battery; 7. a charger; 8. an air inlet pipe; 9. an exhaust pipe; 10. a fuel compartment; 11. a fuel oil pocket; 12. a cable car compartment; 13. a winch; 14. a lower deck; 15. a power amplifier; 16. a battery pack; 17. transmitting an array; 18. receiving an array; 19. a bottom layer electronic unit; 20. array elements; 21. a center pole; 22. a receiving arm; 23. and (5) sinking the blocks.

Detailed Description

The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited to the specific embodiments.

Throughout the specification and claims, unless explicitly stated otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element or component but not the exclusion of any other element or component.

In the description of the present invention, the terms "first" ("first"), "second" ("second"), etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" ("first"), "second" ("second") can explicitly or implicitly include at least one of the feature. Further, "plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.

Reference throughout this specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by a person skilled in the art that the described embodiments can be combined with other embodiments.

Referring to fig. 1, in a preferred embodiment of the present invention, the acoustic buoy apparatus is a medium-large water surface buoy whose sound source can be emitted for a long time and array can be deepened in a wide range, the buoy includes a floating capsule 1 and a buoy body, the buoy body includes a deepening active sonar system, the buoy body can be divided into 4 cabin sections from top to bottom in sequence, including: a surface tank 2, a fuel tank 10, a cable car tank 12 and a bottom tank 14. The floating water surface cabin 2 is internally provided with a generator 3, a charger 7, a starting battery 6, a communication module 4 and a top layer electronic unit 5, the floating bag 1 is arranged on the outer side of the water surface cabin 2, the fuel tank 10 is internally provided with a fuel package 11 for supplying oil to the generator 3, the cable car cabin 12 is internally provided with a winch 13 and a bearing cable, the bottom layer cabin 14 comprises a power amplifier 15 and a battery pack 16, and the buoy further comprises a transmitting array 17, a receiving array 18, a bottom layer electronic unit 19 and other components which are connected to the tail end of the bearing cable.

The fuel in the fuel tank 10 is supplied to the generator 3, the generator 3 generates power to charge the battery pack 16 so as to supply power to the electricity utilization unit of the acoustic buoy, and active detection in deep sea areas for a long time can be realized.

In some embodiments, as shown in fig. 2, the present invention provides a variable depth active acoustic buoy detection method, comprising the steps of:

s1, acquiring information and a remote control instruction;

s2, making a target detection strategy and sending a control command according to the target detection strategy;

and S3, controlling a sonar of the acoustic buoy to send out a detection signal according to the control instruction.

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

In some embodiments, the information includes marine environment information and suspicious target information, the marine environment information includes environmental parameters of the sea area where the acoustic buoy is located, such as water depth, water bottom landform, storm parameters, and the like; the suspicious target intelligence includes one or more of a suspicious target location, a suspicious target type, a suspicious target threat level. The remote control instruction information includes an acoustic buoy instruction for starting up, shutting down, deepening (changing the depths of the transmitting array 17 and the receiving array 18), changing transmission (changing the type/frequency band/bandwidth/pulse width of a transmitting signal, transmitting interval, transmitting power, transmitting direction and the like), starting transmission, stopping transmission, removing the battery pack 16, self-destruction and the like, and is used for controlling the transmitting signal, the posture and the working state of the acoustic buoy.

In some embodiments, the informative information further comprises: acoustic buoy status information including one or more of a geographic location of the acoustic buoy, a receiving array 18 attitude, and a drift velocity. Here, the state information of the acoustic buoy is positioning calibration data transmitted from an external positioning system such as a satellite or a base station, and is used by the positioning module, and the positioning module calculates the position and drift velocity information of the acoustic buoy according to the positioning calibration data, and transmits the information to the top layer electronic unit 5 and the bottom layer electronic unit 19.

The emission control of the detection signal is that the top layer electronic unit 5 sends a control signal to the power amplifier 15 and generates a multi-channel emission signal, the multi-channel emission signal is amplified according to the ordered power by the power amplifier 15 and then sent to the emission array 17, and the emission array 17 performs electro-acoustic conversion and radiates an acoustic signal into water according to the appointed vertical beam control (horizontal omnidirectional beam control). The multichannel transmitting signal is derived from a single-channel basic transmitting waveform, the number of channels is the same as the number of array elements of a transmitting array 17, and the time delay difference of each channel is determined according to vertical beam control calculation.

Further, referring to fig. 3, the top layer electronic unit 5 in the acoustic buoy formulates a target detection strategy according to the acquired information, remote control instruction and state information, and specifically includes the following steps:

s201: a predetermined probing strategy is provided. The preset detection strategy is preset in advance in a memory within the top layer electronics unit 5 of the acoustic buoy.

S202: and generating detection parameters according to a preset detection strategy, information and a remote control instruction. The detection parameters mainly include: transmitting a signal waveform, a signal transmission control instruction and a deepening instruction;

s203: performing sound field modeling based on the detection parameters and different acoustic propagation effects,

s204: performing performance forecasting based on the sound field modeling result, and evaluating whether the detection range and the detection probability of the sonar under the current working parameters and the sound propagation effect meet the preset requirements or not according to the performance forecasting result; if so, taking the detection strategy corresponding to the current detection parameter as a target detection strategy; if not, adjusting the detection parameters, and returning to step S203.

Here, steps S203 to S204 are automatic optimization steps of the target detection strategy, and further refer to fig. 4, which is specifically divided into three parts:

t1. Policy generation section. The target detection strategy comprises two aspects of variable emission and variable depth, and the establishment of the optimal strategy is essentially the optimization of sonar emission and array depth related working parameter setting and flow control, so that a sonar working parameter optimizing component is a core component generated by the target detection strategy. The input of the component comprises preset parameter setting obtained through a preset detection strategy, remote control parameter setting obtained through a user remote control instruction and parameter adjustment under sonar performance inspection. The temporary output comprises a series of emission and array depth parameters such as emission array depth, receiving array depth, emission direction and beam control, reception direction and beam control, emission power or source level, emission signal type, emission frequency band and bandwidth, emission pulse width and interval and the like, and the temporary output is used as the equipment condition input of the sound field modeling part. And the optimized and adjusted parameters are used as the final output of the component, enter a target detection strategy generation component, and are matched with a time sequence flow to form a final target detection strategy, wherein the final target detection strategy comprises three types of information, namely emission waveform, emission control instruction and deepening instruction.

T2. Sound field modeling section. The core component of the part is diversified acoustic propagation effect modeling, and is one of the characteristic functional embodiments of the acoustic buoy, and one or more of multiple acoustic propagation effects such as direct sound path, deep sea sound channel, first convergence region, reliable sound path, seabed reflection and the like are selected to be presented according to input emission, array depth, environment and target conditions to perform underwater sound field modeling, including corresponding sea surface scattering, seabed scattering, target scattering and environmental noise modeling. There are three types of input parameters: firstly, transmitting signals, receiving and transmitting array depth and receiving and transmitting pointing parameters temporarily output by a sonar working parameter optimizing component in T1; the marine environment information transmitted by presetting or remote control comprises sea surface parameters (sea conditions, wave heights, sea surface scattering coefficients and the like), seabed parameters (bottom material types, layering and seabed scattering coefficients), sea depths, seabed topography, sound velocity profiles, mesoscale flow parameters, background noise levels and the like; and thirdly, presetting or remotely controlling transmitted marine target information, wherein the marine target information comprises the type, position, size, speed and the like of the sea surface large target and the underwater suspicious target. The sound field modeling result, i.e., the final output of the component, will enter the performance prediction section.

And T3, a performance forecasting part. Based on sound field modeling, a series of calculations such as propagation loss prediction, reverberation level prediction, sonar working distance prediction, sonar detection probability estimation, seabed clutter intensity and bright spot structure prediction, target intensity and bright spot structure prediction and the like are carried out, the detection range and detection probability of the sonar under the current working parameters and sound propagation path are evaluated so as to judge whether the sonar achieves the best performance and possible parameter setting improvement, a sonar working parameter optimizing component in T1 is fed back, and a new round of flow of 'parameter setting → sound field modeling → performance prediction' is carried out. This loop is repeated until a parameter setting scheme is obtained that meets the performance requirements.

In addition, in some embodiments, the target echo and background interference feature forecast can also be provided by using the mathematical model and detection parameters established in the target detection strategy optimizing step. The target echo and background interference characteristic forecasting refers to modeling and forecasting of target echo and background interference characteristics: based on various parameter calculation in sound field modeling and sonar performance forecasting, space-time frequency feature description of signals such as target echoes, reverberation and seabed clutter under a current sonar working mode, which is matched with target and environment information, is given physically or numerically. Theoretically, under optimized sonar working parameters, target detection is carried out according to strategies, and target echoes and background interference in received signals should have the characteristics which are identical with forecast. This feature prediction is therefore an important basis for the subsequent implementation of signal processing adapted to the environmental and target features.

The echo signal is a multichannel array element level signal which is transmitted out, reflected by a target or a barrier, received by the array element of the receiving array 18, subjected to acousto-electric conversion by the receiving array 18 and transmitted to the bottom layer electronic unit 19. The subsequent signal processing is to perform data processing on the multi-channel array element level signals, as shown in fig. 5.

In some embodiments, the step S3 is followed by a step of processing an echo signal, which specifically includes:

s4: and receiving an echo signal and carrying out signal processing on the echo signal.

S5: and generating a detection picture according to the output of the signal processing.

S6: and processing the detection pictures accumulated by the PINGs to form a target point trace, and further automatically identifying and evaluating the target attributes and threat levels to generate a target detection result.

S7: and sending the target detection result to an external terminal.

With further reference to fig. 6, in some embodiments, the step of signal processing the echo signals comprises:

s401: and extracting effective acquisition signals from the received echo signal data according to a data transmission protocol, and performing normalization on a dynamic range and a time-space sequence to form multi-channel array element level signal data.

S402: filtering and homogenizing multi-channel array element level signal data; the method comprises the following steps:

band-pass filtering and scale filtering. And extracting the current transmitting frequency band and bandwidth according to the transmitting control instruction, and calculating a distance resolution element and a maximum resolution scale, thereby setting the band-pass filtering and scale filtering range and filtering the input data.

And (4) pre-homogenizing. And the homogenization treatment is designed and implemented according to the characteristics of reverberation and clutter, so that the non-stationary non-Gaussian non-whiteness of data is reduced, and the dynamic range of the data is reduced.

Constant low side lobe spatial filtering. And (3) designing and implementing constant low sidelobe spatial filtering according to the array spread state to reduce sidelobe interference, and splitting the space into a left sub-array beam and a right sub-array beam for output.

S403: calculating and suppressing the Doppler frequency shift and the expansion of local reverberation in the appointed wave beam direction according to the drifting direction and speed of the acoustic buoy and the parameters of a transmitting signal; preferably, a nulling filter is used for suppression.

S404: and respectively generating series signal copies of the multi-wavelet multi-speed channel for the two sub-array beams according to the transmitted waveform and the target echo characteristic forecast, and then performing matched filtering on the copies one by one. The multi-wavelet includes both the combined wavelet of the combined signal and the bright point wavelet of the multi-bright point echo.

S405: the multi-speed matching output of any wavelet corresponds to one ambiguity map, and the multiple ambiguity maps output by the multiple wavelets of any subarray wave beam are subjected to nonlinear fusion so as to obtain the super-resolution capability on a time-frequency joint domain.

S406: based on the fact that a left sub-array beam and a right sub-array beam in the appointed direction are output as a main array beam after matched fusion, the main array beam is subjected to phase unit processing so as to restrain main lobe interference and obtain super-resolution capability on a space-time joint domain.

S407: and performing post-homogenization treatment adaptive to the echo statistical characteristics after super-resolution on the total array beam according to the target echo characteristic prediction and the time-space-frequency super-resolution treatment influence, so that the false alarm can be further reduced.

With further reference to fig. 7, in some embodiments, step S5 comprises:

s501: and generating a relative detection picture. And accumulating, smoothing or resampling the post-homogenized output data into a plane image as a relative detection picture according to the effective display area under the natural coordinate system of the acoustic buoy, and completely refreshing each detection PING of the relative detection picture once. The natural coordinate system of the receiving array 18 of the acoustic buoy refers to a coordinate system constructed by relative azimuth or bulwark-distance-relative radial velocity-data intensity or amplitude.

S502: and carrying out coordinate conversion according to the position of the acoustic buoy, the orientation of the receiving array and the attitude information of the receiving array. The disadvantage of the relative coordinate system is that the motion factors such as the drift of the buoy, the rotation and the inclination of the receiving array 18 or the transmitting array 17 are all taken into account, so that the real motion state of the target cannot be known. After coordinate conversion is designed and implemented according to the position, the array direction and the array posture information of the acoustic buoy, the target state can be further calibrated, and the detection precision is improved.

S503: and taking the plane image after coordinate conversion of the relative detection picture as an absolute detection picture. Through coordinate transformation, the point on the relative detection picture is transformed into a point under a geographic position (longitude-latitude, or transverse and longitudinal displacement referring to a fixed geographic point) -absolute radial velocity-intensity coordinate system. The design is expressed as a planar image according to ergonomics, i.e. an absolute detection picture. The points on the picture have removed the motion effect.

In some embodiments, step S6 comprises:

s601: and calculating a constant false alarm threshold, a target speed limit and a target scale limit according to target echo and background interference characteristic forecast, forming a multi-characteristic comprehensive threshold, automatically detecting data on an absolute detection picture, reserving data which pass the threshold, and nulling the rest data.

S602: and (4) performing target point extraction and contact level tracking on the automatically detected picture data, and dynamically adjusting the weight of position and speed information in the tracking process.

S603: and forming a target point trace according to the contact level tracking result accumulated by the multiple PINGs, performing consistency judgment on the target point trace and the motion rule of the underwater target, correcting the trace data according to the judgment result, returning the corrected data to the step S601, recalculating the multi-feature comprehensive threshold, and repeating the steps S602 and S603. The trace point data is corrected, namely, the target attribute is judged according to the consistency of the trace points and the motion rule of the underwater target, or the trace points which are lost or wrong in tracking are recovered or corrected and reconfigured according to the motion rule, the disordered trace points are abandoned, and the rule formed by stable trace points is fed back to the step S601 to correct the speed limit or the scale limit comprehensive threshold, so that the new automatic detection with lower false alarm is formed.

S604: and according to the accumulation of the automatic detection and tracking results, automatically identifying and evaluating the target attribute and the threat level to form a DLCT result and finish autonomous detection. DLCT results include the location, velocity, scale, type, and threat level of the target.

On the other hand, the embodiment of the invention also provides an acoustic buoy device, which is a load deepening active sonar system, wherein the deepening active sonar system can radiate acoustic pulse signals with high power into water at different depths, receive echo signals of the signals with large aperture and process the signals autonomously, and adopts the deepening active acoustic buoy detection method to detect a target.

In the preferred embodiment of the present invention, the bottom layer electronic unit 19 sends the target detection results to the top layer electronic unit 5 for aggregation and transmission to the user via satellite or wireless communication component.

As shown in fig. 8, in a preferred embodiment of the present invention, the information sent to the user may further include: the target position detection result corresponds to the PING moment, and the real-time monitoring information and the warning information of the state of the acoustic buoy device, wherein the real-time monitoring information comprises: the depth of the receiving array 18 and the transmitting array 17, the temperature and the electric allowance of the battery pack 16, the fuel oil allowance, the state of the generator 3, the state of the charger 7, the state of the winch 13, the cable laying length, the position of the acoustic buoy, the allowance of the top layer unit battery, the allowance of the bottom layer unit battery and the like, and the alarm information comprises: component failure alarm, collision alarm, acoustic array bottoming alarm, high threat target alarm, etc.

In the embodiment of the present invention, the top-level electronic unit 5 is responsible for collecting and summarizing the above information, and transmitting the information to the user through the communication module. The state real-time monitoring information and the alarm information come from each component, and the target detection result comprises a target position (such as azimuth, distance and longitude and latitude), speed, type, threat level and the like; the real-time monitoring information is used for supporting a user to remotely study and judge the working state of the buoy device; the warning information warns the user of abnormal or dangerous states, is real-time, is generated and is sent to the top-level electronic unit 5 and is sent to the user through the satellite or the wireless communication assembly; the position information for the acoustic buoys is received from a satellite or wireless communication component and sent to the user at a particular refresh rate alone or in combination with real-time status monitoring information.

In other embodiments of the present invention, the bottom layer electronic unit 19 may be configured with a signal recorder, and record information such as array element level received signals, array direction, array depth, array attitude, transmitted signals, PING time, mark position, target echo, and background interference characteristic forecast, completely or selectively for a critical time period, so as to provide for offline analysis by a user after recovering acoustic buoy data.

In the preferred embodiment of the invention, a user can remotely change the target detection strategy by sending new remote control instructions and information, thereby realizing remote intervention on the target detection process. The top layer electronic unit 5 is provided with a target detection strategy generation module, and the preset detection strategy is an initial value of the target detection strategy generation module. The requirements of array depth and the requirements of waveform, interval, power and the like of a transmitting signal sent by a user can be used as new working parameter optimizing input, and the target or environment information sent by the user can be used as new condition input of sound field modeling, so that the generation of a new target detection strategy is influenced. After the preset detection strategy and the remote control command and the information jointly support the generation of a new target detection strategy, new control commands and parameters for all related components are immediately sent and executed, and target echo and background interference characteristic forecast information are also timely sent to the bottom layer electronic unit 19 after being updated so as to process target detection signals.

It should be noted that the configuration and the deployment form of the cabin section of the acoustic buoy assembly, the information and signal flow, the target detection strategy generation framework, the received signal processing method framework, and the like shown in the drawings are only corresponding illustrations or examples of respective embodiments, are only used for more clearly illustrating the technical solution of the present invention, and do not constitute a limitation to the content and the technical solution of the present invention.

The foregoing descriptions of specific exemplary embodiments of the present invention have been presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the invention and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the invention and various alternatives and modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.

Claims (10)

1. A method for detecting a variable-depth active acoustic buoy is characterized by comprising the following steps of:

s1, acquiring information and a remote control instruction;

s2, making a target detection strategy and sending a control command according to the target detection strategy;

s3, controlling a sonar of the acoustic buoy to send out a detection signal according to the control instruction;

the step of formulating the target detection strategy comprises the following steps:

s201: providing a preset detection strategy;

s202: generating detection parameters according to a preset detection strategy, information and a remote control instruction;

s203: performing sound field modeling according to the detection parameters and different sound propagation effects;

s204: performing performance forecasting based on the sound field modeling result, and evaluating whether the detection range and the detection probability of the sonar under the current working parameters and the sound propagation effect meet the preset requirements or not according to the performance forecasting result; if so, taking the detection strategy corresponding to the current detection parameter as a target detection strategy; if not, adjusting the detection parameters, and returning to step S203.

2. The method of claim 1, wherein the information comprises sea area environment information and suspicious object information, the sea area environment information comprises environment parameters of a sea area where the acoustic buoy is located, and the suspicious object information comprises one or more of a suspicious object location, a suspicious object type, and a suspicious object threat level.

3. The method of claim 2, wherein the informative information further comprises: state information of the acoustic buoy, the state information of the acoustic buoy including one or more of a position, an attitude, and a drift velocity of the acoustic buoy.

4. The method of claim 1, wherein the acoustic propagation effects comprise one or more of a direct acoustic path, a deep sea acoustic channel, a first convergence zone, a reliable acoustic path, and a sea floor reflection;

the performance forecast comprises one or more of propagation loss, reverberation level, sonar working distance, sonar detection probability, sea bottom clutter intensity and bright spot structure, target intensity and bright spot structure.

5. The method of claim 1, wherein the detection parameters include transmit signal waveform, signaling commands, and depth commands.

6. The method according to claim 5, wherein the target detection strategy further comprises providing a target echo and background interference feature forecast, wherein the target echo and background interference feature forecast comprises a space-time-frequency basic feature forecast of one or more background interferences of target echo and noise, reverberation and sea bottom clutter in a current sonar operation mode.

7. The method of claim 6, further comprising, after step S3:

s4: receiving an echo signal and carrying out signal processing on the echo signal;

s5: generating a detection picture according to the output of the signal processing;

s6: processing the detection pictures accumulated by the PINGs to form a target point trace, and further automatically identifying and evaluating target attributes and threat levels to generate a target detection result;

s7: and sending the target detection result to an external terminal.

8. The method of claim 7, wherein the signal processing comprises:

s401: extracting effective acquisition signals from received echo signal data according to a data transmission protocol, and carrying out normalization on a dynamic range and a time-space sequence to form multi-channel array element level signal data;

s402: filtering and homogenizing multi-channel array element level signal data, wherein the filtering and homogenizing processing comprises band-pass filtering, scale filtering, prepositive homogenizing and constant low side lobe space filtering; splitting multi-channel array element level signal data into a left sub-array beam and a right sub-array beam for output;

s403: calculating and suppressing the Doppler frequency shift and the expansion of local reverberation in the appointed wave beam direction according to the drifting direction and speed of the acoustic buoy and the parameters of a transmitting signal;

s404: according to the transmitted waveform and target echo characteristic forecast, respectively generating series signal copies of a multi-wavelet multi-speed channel for two sub-array beams, and then carrying out matched filtering on the copies one by one;

s405: the multi-speed matching output of any wavelet corresponds to a ambiguity map, and the multiple ambiguity maps output by the multiple wavelets of any subarray wave beam are subjected to nonlinear fusion to obtain the super-resolution capability on a time-frequency joint domain;

s406: based on the fact that a left sub-array beam and a right sub-array beam in the designated direction are matched and fused to serve as a main array beam to be output, phase unitization processing is conducted on the main array beam to inhibit main lobe interference and obtain super-resolution capability on a space-time joint domain;

s407: and performing post-homogenization treatment adaptive to the echo statistical characteristics after super-resolution on the total array beam according to the target echo characteristic prediction and the influence of time-space-frequency super-resolution treatment.

9. The method of claim 8, wherein the method further comprises the step of,

step S5 comprises the following steps:

s501: accumulating, smoothing or resampling the post-homogenized output data into a plane image as a relative detection picture according to the effective display area under a natural coordinate system of the acoustic buoy, and completely refreshing each detection PING of the relative detection picture once;

s502: performing coordinate conversion according to the position of the acoustic buoy, the orientation of the receiving array and the attitude information of the receiving array;

s503: taking the plane image of the relative detection picture after coordinate conversion as an absolute detection picture;

step S6 comprises:

s601: calculating a constant false alarm threshold, a target speed limit and a target scale limit according to target echo and background interference characteristic forecast, forming a multi-characteristic comprehensive threshold, automatically detecting data on an absolute detection picture, reserving data passing the threshold, and nulling the rest data;

s602: carrying out target point extraction and contact level tracking on the automatically detected picture data;

s603: forming a target point trace according to a contact level tracking result accumulated by the PINGs, performing consistency judgment on the target point trace and an underwater target motion rule, correcting trace data according to a judgment result, returning the corrected data to the step S601, recalculating the multi-feature comprehensive threshold, and repeating the steps S602 and S603;

s604: and according to the accumulation of the automatic detection and tracking results, automatically identifying and evaluating the target attribute and the threat level to form a DLCT result and finish autonomous detection.

10. An acoustic buoy device, characterized in that the acoustic buoy device is a load-deepening active sonar system and adopts the deepening active acoustic buoy detection method according to any one of claims 1 to 9 for target detection.

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