Method, device and electronic equipment for classifying and identifying buoy communication signals

Abstract

The present invention provides a classification and identification method, device and electronic equipment for buoy communication signals, and relates to the technical field of data processing. The method is applied to a shipborne display and control platform of a signal recording buoy system, and the signal recording buoy system also includes a buoy, and the buoy and the shipborne display and control platform transmit data. The method comprises: determining a time-frequency spectrum and a characteristic value of the communication signal based on a pre-acquired communication signal of the buoy; determining a first type of communication signal and a second type of communication signal according to characteristic parameters of the time-frequency spectrum; and classifying the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the communication signal, thereby solving the technical problem that the analysis of the buoy communication signal is not accurate enough and achieving the technical effect of improving the classification and identification accuracy of the communication signal.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device and electronic equipment for classifying and identifying buoy communication signals. Background Art

[0002] The signal recording buoy system consists of a signal recording buoy (wet end), a deck unit and a shipboard display and control platform (dry end). The signal recording buoy has the function of long-term listening to ocean acoustic data, monitoring and recording signals, and autonomously identifying the center frequency, bandwidth, bit rate and modulation mode of communication signals. The deck unit is a matching dry-end device for the signal recording buoy, which can generate multiple sets of ranging signals and remote control command signals for recording buoys. The shipboard display and control platform is the signal processing center of the dry-end equipment, which can not only complete the position calibration function of the underwater recording buoy, but also perform signal detection and identification, thereby evaluating the probability of the existence of the communication signal, and identifying the modulation mode of the communication signal to obtain more data information. However, there is a technical problem in the technical solution of the prior art for buoy signal identification that the identification and classification of signals are not accurate enough. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device and electronic device for classifying and identifying buoy communication signals, so as to alleviate the technical problem of inaccurate classification and identification of signals existing in the prior art.

[0004] In a first aspect, an embodiment of the present invention provides a classification and identification method for a submerged buoy communication signal, which is applied to a shipborne display and control platform of a signal recording submerged buoy system, wherein the signal recording submerged buoy system further includes a submerged buoy, and the submerged buoy performs data transmission with the shipborne display and control platform; the method includes:

[0005] Based on the pre-acquired buoy communication signal, determining the time-frequency spectrum and characteristic value of the buoy communication signal;

[0006] Determine the classification of the above-mentioned buoy communication signal according to the characteristic parameter of the number of peaks of the above-mentioned time-frequency spectrum; the types of the above-mentioned buoy communication signal include: first-type communication signals and second-type communication signals;

[0007] The first type of communication signal and the second type of communication signal are classified based on the characteristic values ​​to determine the modulation signal of the latent beacon communication signal.

[0008] In some possible implementations, the method further includes: determining the communication signal of the buoy based on pre-acquired ocean acoustic data; wherein the ocean acoustic data is collected by the buoy and sent to the shipborne display and control platform.

[0009] In some possible implementations, the above-mentioned characteristic values ​​include a first characteristic value, a second characteristic value, a third characteristic value, a fourth characteristic value and a fifth characteristic value; the above-mentioned first-category communication signal and the above-mentioned second-category communication signal are classified respectively based on the above-mentioned characteristic values, including: according to the above-mentioned first characteristic value, the above-mentioned second-category communication signal is divided into three sub-types of MAM, MPSK and MQAM; according to the above-mentioned third characteristic value, the above-mentioned fourth characteristic value and the above-mentioned fifth characteristic value, the above-mentioned first-category communication signal is divided into three sub-types of 2FSK, 4FSK and 8FSK; according to the above-mentioned second characteristic value, the sub-types after the above-mentioned second-category communication signal is divided are classified.

[0010] In some possible implementations, the subtypes after the second category of communication signals are divided are classified according to the second characteristic value, including: according to the second characteristic value, the MPSK subtypes after the second category of communication signals are divided are divided into 2PSK, 4PSK and 8PSK; according to the second characteristic value, the MQAM subtypes after the second category of communication signals are divided are divided into 8QAM, 16QAM and 64QAM.

[0011] In some possible implementations, before determining the time-frequency spectrum and characteristic values ​​of the communication signal based on the communication signal of the beacon acquired in advance, the method includes: determining multiple time-frequency characteristic values ​​of the communication signal based on the communication signal of the beacon acquired in advance; and determining that the type of the communication signal is a continuous broadband communication signal based on the time-frequency characteristic values.

[0012] In some possible implementations, determining the characteristic value of the communication signal based on the pre-acquired communication signal of the latent beacon includes: calculating the moment function of the high-order cumulative amount based on the pre-acquired communication signal of the latent beacon, and obtaining the characteristic value of the communication signal based on the moment function.

[0013] In a second aspect, an embodiment of the present invention provides a classification and identification device for a latent buoy communication signal, comprising: a first determination module, configured to determine a time-frequency spectrum and a characteristic value of the latent buoy communication signal based on a pre-acquired latent buoy communication signal;

[0014] A second determination module is used to determine the classification of the above-mentioned buoy communication signal according to the characteristic parameters of the above-mentioned time-frequency spectrum; the types of the above-mentioned buoy communication signal include: a first type of communication signal and a second type of communication signal;

[0015] The classification module is used to classify the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the latent buoy communication signal.

[0016] In some possible implementations, the first determination module is further used to: determine the communication signal of the buoy based on pre-acquired ocean acoustic data; wherein the ocean acoustic data is collected by the buoy and sent to the shipborne display and control platform. In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of any one of the methods described in the first aspect are implemented.

[0017] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores machine-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to execute any method described in the first aspect.

[0018] The present invention provides a method, device and electronic equipment for classifying and identifying communication signals of a buoy. The method is applied to a shipborne display and control platform of a signal recording buoy system. The signal recording buoy system also includes a buoy, and the buoy and the shipborne display and control platform perform data transmission. The method comprises: determining a time-frequency spectrum and a characteristic value of the communication signal based on a pre-acquired communication signal of the buoy; determining a first type of communication signal and a second type of communication signal according to characteristic parameters of the time-frequency spectrum; classifying the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the communication signal, thereby solving the technical problem that the analysis of the buoy communication signal is not accurate enough and achieving the technical effect of improving the classification and identification accuracy of the communication signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic diagram of a flow chart of a method for classifying and identifying a latent buoy communication signal provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of a downlink communication signal design provided by an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the principle of a method for classifying and identifying latent buoy communication signals provided by an embodiment of the present invention;

[0023] Figure 4A schematic diagram of a communication instruction receiving process provided by an embodiment of the present invention;

[0024] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. Some embodiments of the present invention are described in detail below in conjunction with the drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] The signal recording buoy system consists of a signal recording buoy, a deck unit and a shipboard display and control platform. The signal recording buoy has the function of long-term listening to ocean acoustic data, monitoring and recording signals, and autonomously identifying the center frequency, bandwidth, bit rate and modulation mode of communication signals. The deck unit is a supporting dry-end device for the signal recording buoy, which can generate multiple sets of ranging signals and remote control command signals for recording buoys. The shipboard display and control platform is the signal processing center of the dry-end equipment, which can not only complete the position calibration function of the underwater recording buoy, but also perform signal detection and identification, thereby evaluating the probability of the existence of the communication signal, and identifying the modulation mode of the communication signal to obtain more data information. However, there is a technical problem in the technical solution of the prior art for buoy signal identification that the identification and classification of signals are not accurate enough.

[0029] Based on this, the embodiments of the present invention provide a method, device and electronic device for classifying and identifying buoy communication signals to alleviate the technical problem of inaccurate classification and identification of signals in the prior art.

[0030] To facilitate understanding of this embodiment, firstly, a classification and identification method of a latent buoy communication signal disclosed in an embodiment of the present invention is described in detail, see Figure 1 A flow chart of a method for classifying and identifying a buoy communication signal is shown, and Figure 2 The schematic diagram of the principle of a classification and identification method for a buoy communication signal is shown. The method is applied to a shipborne display and control platform of a signal recording buoy system. The signal recording buoy system also includes a buoy, and the buoy transmits data with the shipborne display and control platform.

[0031] The signal recording buoy is composed of a signal acquisition and storage module, a signal autonomous detection and identification module, a response and ranging module, an underwater acoustic remote control communication module, a Beidou positioning module, a strobe module, a radio frequency identification module, a self-destruct module, a status self-check module, a program upgrade module, a power supply system, a release device, an acoustic transducer, an acoustic hydrophone and a watertight hull.

[0032] The deck unit consists of a distance measurement module, a remote control communication module, a Beidou positioning module, a power supply system and an acoustic transducer. The shipboard display and control platform consists of a positioning solution module, a data analysis and processing module, a data cleaning module, a display control interface and a disk array.

[0033] Among them, the signal recording buoy has the function of long-term listening to ocean acoustic data, monitoring and recording signals, and autonomously identifying the center frequency, bandwidth, code rate and modulation mode of communication signals; it supports hydroacoustic calibration function, uses the deck unit with its own absolute position information, inquires and responds to the recording buoy, completes the distance measurement, and uses the long baseline circling positioning method to accurately calibrate the absolute position of the buoy on the seabed. The recording buoy supports hydroacoustic remote control release function, controls the fuse, releases the sinking coupling frame, and automatically recovers. When it floats to the sea surface, it flashes to indicate its position. On the ship-borne display and control platform, the Beidou positioning system is used to locate the absolute position of the buoy to achieve highly reliable recovery; it supports high-speed USB3.0 data communication interface, which can quickly export raw data; the radio frequency identification module supports the recording of the buoy's address code, settings and status parameter self-test functions.

[0034] The deck unit is a supporting dry-end device for the signal recording buoy, which can generate multiple sets of ranging signals and remote control command signals for recording buoys. It actively transmits ranging signals, starts timing and records the absolute position information at the time of transmission, receives multiple sets of buoy ranging response signals, and when the ranging signal is detected, stops timing and records the absolute position information at the time of reception, and calculates the two-way delay difference between the deck unit and the recording buoy. The long baseline positioning algorithm is used, and the delay difference information and sound velocity profile are substituted to realize the positioning of the recording buoy. It generates complex acoustic wave signals with address information, command information, user information and password samples to ensure the security and reliability of the signal and increase the difficulty of deciphering the information.

[0035] The shipboard display and control platform is the signal processing center of the dry-end equipment. It can receive Beidou position information, sound velocity profile information and slant range information of the deck unit, complete the position calibration function of the underwater recording buoy, and calculate the current position of the recording buoy in real time, and predict its trajectory and its accurate landing point. It can use the multi-eigenvalue analysis and processing method for the recorded acoustic data to accurately identify its modulation mode.

[0036] Based on this, the classification and identification method of the submerged buoy communication signal applied to the shipborne display and control platform provided in this embodiment mainly includes the following steps S110 to S130:

[0037] S110: Determine the time-frequency spectrum and characteristic value of the latent buoy communication signal based on the pre-acquired latent buoy communication signal;

[0038] S120: Determine the classification of the buoy communication signal according to the characteristic parameters of the time-frequency spectrum; the types of the buoy communication signal include: a first type of communication signal and a second type of communication signal;

[0039] The buoy communication signal can be any one or a combination of MFSK, MAM, MPSK, and MQAM. MFSK is a modulation method that can use multiple different carrier frequencies to represent a variety of digital information; MAM is an amplitude modulation signal; MPSK is a multi-level digital phase modulation, also known as a multi-phase system, which is a generalization of a two-phase system; MQAM is a multi-level orthogonal amplitude modulation.

[0040] In this embodiment, the received buoy communication signal can be down-converted to obtain a baseband complex signal, and then a fast Fourier transform FFT is performed to first identify and classify the buoy communication signal into a first type of communication signal (MFSK) and a second type of communication signal (MAM, MPSK, MQAM) in the frequency domain. Then, the buoy communication signal is identified and processed according to the characteristic parameters, and multiple characteristic values ​​of the signal are extracted. The change in the signal characteristic value is statistically calculated, and finally the modulation mode of the signal is detected, analyzed and identified.

[0041] S130: Classify the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the latent buoy communication signal.

[0042] In one embodiment, the above method may further include: determining the communication signal of the submerged buoy based on pre-acquired ocean acoustic data; wherein the ocean acoustic data is collected by the submerged buoy and sent to the ship-borne display and control platform.

[0043] In one embodiment, before determining the time-frequency spectrum and characteristic values ​​of the communication signal based on the communication signal of the pre-acquired potential beacon, the method includes: determining multiple time-frequency characteristic values ​​of the communication signal based on the communication signal of the pre-acquired potential beacon; and determining that the type of the communication signal is a continuous broadband communication signal based on the time-frequency characteristic values.

[0044] In one embodiment, determining the characteristic value of the communication signal based on the pre-acquired communication signal of the latent beacon includes: calculating the moment function of the high-order cumulant based on the pre-acquired communication signal of the latent beacon to obtain the characteristic value of the communication signal based on the moment function.

[0045] The underwater acoustic remote control communication module in the signal recording buoy system consists of two parts: the transmitting module and the receiving module. Both the transmitting and receiving modules are implemented using time division and frequency division schemes, and different time division and frequency division combinations represent different data information.

[0046] The underwater acoustic remote control communication module adopts a time delay coding scheme and a design of three 3-frequency pulse periodic repeated transmissions. Each pulse is designed with unused time slots to complete the modulation of different data information and the information transmission of underwater acoustic remote control commands.

[0047] The inquiry signal is designed as Figure 3 As shown in the schematic diagram of a downlink communication signal design provided, the buoy needs to receive and detect the communication group number and communication command code of the buoy, complete the identification of the group number and the analysis of the command code, and complete different functional operations according to the command code. The communication signal detection process of the buoy can be found in Figure 4 The schematic diagram of a communication instruction receiving and processing flow shown includes: MCU collects communication pulses; determines whether the pulse interval is met; if it is met, saves each pulse delay, if not, re-collects; determines whether all pulses have been collected; if so, performs delay analysis to determine whether the communication instruction protocol is met; if it is met, executes the corresponding operation of the instruction, and replies to the hydroacoustic instruction; if not, re-collects the first pulse. When the buoy completes the reception of the communication instruction, it completes the protocol analysis according to the instruction protocol, and performs functional operations such as release, voltage detection, noise detection, etc., and completes the data encapsulation, communication reply signal generation and transmission according to the protocol.

[0048] The intercepted data analysis and identification software can read the communication signal of the recorded buoy according to the work log of the recorded buoy, and re-analyze and process the specific acoustic data. The time-frequency spectrum of the signal is quickly calculated and analyzed to obtain the center frequency change and bandwidth change of the signal. The time-frequency feature quantity, high-order cumulant and cyclic spectrum are calculated, and the feature parameters are extracted according to the spectrum characteristics, and the modulation mode is identified. Blind demodulation and blind equalization are performed according to the modulation mode to obtain more data information.

[0049] In one embodiment, the characteristic values ​​include a first characteristic value, a second characteristic value, a third characteristic value, a fourth characteristic value and a fifth characteristic value; the first type of communication signal and the second type of communication signal are classified based on the characteristic values, including: according to the first characteristic value, the second type of communication signal is divided into three subtypes of MAM, MPSK and MQAM; according to the third characteristic value, the fourth characteristic value and the fifth characteristic value, the first type of communication signal is divided into three subtypes of 2FSK, 4FSK and 8FSK; according to the second characteristic value, the subtypes of the second type of communication signal are classified.

[0050] In one embodiment, the subtypes after the second category of communication signals are divided are classified according to the second characteristic value, including: according to the second characteristic value, the MPSK subtypes after the second category of communication signals are divided into 2PSK, 4PSK and 8PSK; according to the second characteristic value, the MQAM subtypes after the second category of communication signals are divided into 8QAM, 16QAM and 64QAM.

[0051] As a specific example, assuming that the random process x has a probability density distribution function f(x), its characteristic function is defined as:

[0052]

[0053] The characteristic function Φ(w) is the probability density distribution function; f(x) is the Fourier transform. Since f(x) ≥ 0, the characteristic function Φ(w) has a maximum value at the origin. That is, the characteristic function satisfies:

[0054] |Φ(w)|≤Φ(0)=1

[0055] The set of real random variables [x1,x2,…,x n ] is the union of γ=k1+k2+…+k n The order cumulant is defined as:

[0056]

[0057] For the zero-mean stationary complex random process X, five classification features F1, F2, F3, F4, F5 are defined, and combined with the characteristics of the signal frequency spectrum, the classification and recognition of MAM, MPSK (absolute phase modulation), MQAM and MFSK signals are completed.

[0058] The feature quantities F1, F2, F3, F4, and F5 are defined as follows:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] Among them, the parameters used in the above formula (C 63 , C 42 , C 40 , C 41 , C 42 , C 60 , C 20 …) That is, the parameters of different modulation signals are fixed, and the characteristic values ​​are also fixed. The buoy equipment analyzes the collected signals and performs FFT calculations to obtain F1, F2, F3, F4, and F5 for classification and identification of different signals. The specific parameters of different combinations of F1, F2, F3, F4, and F5 for classification and identification are detailed in Tables 1 to 4 below. For MAM, MPSK, MQAM, and MFSK signals, the advantage of using characteristic quantities F1, F2, F3, F4, and F5 is that they have different energy E s The phase θ is invariant, that is, the characteristic values ​​F1, F2, F3, F4, and F5 are invariant to the amplitude scaling and phase rotation of the signal constellation diagram. And the characteristic value can also remain relatively stable under the fading channel model.

[0065] Table 1 - Coefficients of Eigenvalue 1 of Different Modulation Signals

[0066] Modulation type <![CDATA[F1]]> CW 33.356 BPSK 32 QPSK 16 8PSK 16 8QAM 13.812 16QAM 13.759 64QAM 13.618

[0067] Table 2 - Coefficients of Eigenvalue 2 of Different Modulation Signals

[0068]

[0069] Table 3 - Coefficients of Eigenvalue 2 of Different Modulation Signals

[0070]

[0071] Table 4 - Coefficients of different modulation signal eigenvalues ​​3, 4, 5

[0072]

[0073] (1) Down-convert the received signal to obtain a baseband complex signal, then perform FFT and determine whether the signal is {MFSK} or {MAM, MPSK, MQAM} based on the number of peaks in the signal spectrum;

[0074] (2) Calculate the high-order cumulants and eigenvalues ​​F1, F2, F3, F4, F5 of the signal;

[0075] (3) According to the eigenvalue F1, the identified {MAM, MPSK, MQAM} are divided into three categories: {MAM}, {MPSK}, {MQAM}; according to the eigenvalues ​​F3F4F5, MFSK is divided into three categories: {2FSK}, {4FSK}, {8FSK};

[0076] (4) According to the characteristic value F2, {MPSK} is divided into {2PSK}, {4PSK}, {8PSK}, and {MQAM} is divided into {8QAM}, {16QAM}, {64QAM}.

[0077] The signal detection and identification processing function includes the signal detection function and the signal identification function. The signal detection function is to analyze and count the time-frequency characteristics of the received signal in real time, and evaluate the probability of the communication signal existing according to the time domain characteristics and frequency domain characteristics of the received signal.

[0078] The purpose of signal modulation is mainly to send information in a form that is easy to transmit and receive. In computer communications, modulation is the conversion of digital signals into analog signals for transmission over the network. In radio communications, modulation is to facilitate the transmission and reception of information signals.

[0079] The communication signal modulation mode identification algorithm proposed in this embodiment adopts a time-frequency characteristic analysis algorithm and a high-order cumulant joint evaluation function to calculate multiple time-frequency characteristic values ​​of the signal to determine whether the signal is a CW signal, an LFM signal, or a continuous broadband communication signal. For a continuous broadband communication signal, the moment function of the high-order cumulant is calculated to obtain the characteristic values ​​F1, F2, F3, F4, and F5 based on the moment function. According to the differences in the characteristic values ​​of different modulation signals, multiple modulation signals such as MAM, 2FSK, MFSK, BPSK, QPSK, 8PSK, 16QAM, and 64QAM are identified.

[0080] In addition, an embodiment of the present invention further provides a device for classifying and identifying latent buoy communication signals, the device comprising:

[0081] A first determination module is used to determine the time-frequency spectrum and characteristic values ​​of the latent buoy communication signal based on the pre-acquired latent buoy communication signal;

[0082] The second determination module is used to determine the classification of the buoy communication signal according to the characteristic parameters of the time-frequency spectrum; the types of the buoy communication signal include: a first type of communication signal and a second type of communication signal;

[0083] The classification module is used to classify the first type of communication signal and the second type of communication signal respectively based on the characteristic value to determine the modulation signal of the latent buoy communication signal.

[0084] In one embodiment, the first determination module is further used to: determine the communication signal of the submerged buoy based on pre-acquired ocean acoustic data; wherein the ocean acoustic data is collected by the submerged buoy and sent to the ship-borne display and control platform.

[0085] The embodiments of the present application provide a method, device and electronic device for classifying and identifying communication signals of a buoy. The method is applied to a shipborne display and control platform of a signal recording buoy system. The signal recording buoy system also includes a buoy, and the buoy transmits data with the shipborne display and control platform. The method includes: determining a time-frequency spectrum and a characteristic value of the communication signal based on a pre-acquired communication signal of the buoy; determining a first type of communication signal and a second type of communication signal according to the characteristic parameters of the time-frequency spectrum; classifying the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the communication signal, thereby solving the technical problem that the analysis of the buoy communication signal is not accurate enough and achieving the technical effect of improving the classification and identification accuracy of the communication signal.

[0086] The classification and identification device for buoy communication signals provided in the embodiment of the present application can be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in the embodiment of the present application are the same as those of the aforementioned method embodiment. For the sake of brief description, the parts not mentioned in the device embodiment can refer to the corresponding contents in the aforementioned method embodiment. Technical personnel in the relevant field can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here. The classification and identification device for buoy communication signals provided in the embodiment of the present application has the same technical features as the classification and identification method for buoy communication signals provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0087] An embodiment of the present application further provides an electronic device. Specifically, the electronic device includes a processor and a storage device. The storage device stores a computer program, and when the computer program is executed by the processor, it executes the method described in any one of the above-mentioned embodiments.

[0088] Figure 5 A structural schematic diagram of an electronic device provided in an embodiment of the present application, the electronic device 400 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43, wherein the processor 40, the communication interface 43 and the memory 41 are connected via the bus 42; the processor 40 is used to execute an executable module stored in the memory 41, such as a computer program.

[0089] The memory 41 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 43 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0090] The bus 42 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0091] Among them, the memory 41 is used to store programs, and the processor 40 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 40 or implemented by the processor 40.

[0092] The processor 40 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 40. The above processor 40 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor to execute, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 41, and the processor 40 reads the information in the memory 41 and completes the steps of the above method in combination with its hardware.

[0093] Corresponding to the above method, an embodiment of the present application also provides a computer-readable storage medium, which stores machine-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the steps of the above method.

[0094] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0095] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0096] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0097] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, electronic device, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0098] It should be noted that similar numbers and letters represent similar items in the accompanying drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for classifying and identifying buoy communication signals, characterized in that: A shipborne display and control platform applied to a signal recording submerged buoy system, wherein the signal recording submerged buoy system further comprises a submerged buoy, and the submerged buoy performs data transmission with the shipborne display and control platform; the method comprises: Based on the pre-acquired ocean acoustic data, the communication signal of the submerged buoy is determined; wherein the ocean acoustic data is collected by the submerged buoy and sent to the ship-borne display and control platform; Based on the pre-acquired buoy communication signal, determining the time-frequency spectrum and characteristic value of the buoy communication signal; Determine the classification of the buoy communication signal according to the characteristic parameters of the time-frequency spectrum; the types of the buoy communication signal include: a first type of communication signal and a second type of communication signal; the first type of communication signal is MFSK, and the second type of communication signal includes: MAM, MPSK, MQAM; Classifying the first type of communication signal and the second type of communication signal respectively based on the characteristic values ​​to determine the modulation signal of the latent beacon communication signal; The eigenvalues ​​include a first eigenvalue, a second eigenvalue, a third eigenvalue, a fourth eigenvalue and a fifth eigenvalue; Classifying the first category of communication signals and the second category of communication signals respectively based on the characteristic values ​​includes: According to the first characteristic value, the second type of communication signal is divided into three subtypes: MAM, MPSK and MQAM; According to the third characteristic value, the fourth characteristic value and the fifth characteristic value, the first type of communication signal is divided into three subtypes of 2FSK, 4FSK and 8FSK; The subtypes into which the second type of communication signals are divided are classified according to the second characteristic value.

2. The method according to claim 1, characterized in that Classifying the subtypes of the second type of communication signals according to the second characteristic value includes: According to the second characteristic value, the MPSK subtypes after the second type of communication signals are divided are divided into 2PSK, 4PSK and 8PSK; According to the second characteristic value, the MQAM subtypes after the second type of communication signals are divided are divided into 8QAM, 16QAM and 64QAM.

3. The method according to claim 1, characterized in that Before determining the time-frequency spectrum and characteristic value of the communication signal based on the pre-acquired communication signal of the latent beacon, the method includes: Based on the pre-acquired communication signal of the latent beacon, determining a plurality of time-frequency characteristic values ​​of the communication signal; The type of the communication signal is determined to be a continuous broadband communication signal based on the time-frequency characteristic value.

4. The method according to claim 3, characterized in that Determining a characteristic value of the communication signal based on the pre-acquired communication signal of the latent marker includes: Based on the pre-acquired communication signal of the buoy, the moment function of the high-order cumulative amount is calculated to obtain the characteristic value of the communication signal based on the moment function.

5. A classification and identification device for latent buoy communication signals, characterized in that: include: A first determination module is used to determine the time-frequency spectrum and characteristic values ​​of the latent buoy communication signal based on the pre-acquired latent buoy communication signal; The first determination module is further used to: determine the communication signal of the submerged buoy based on the pre-acquired ocean acoustic data; wherein the ocean acoustic data is collected by the submerged buoy and sent to the ship-borne display and control platform; A second determination module is used to determine the classification of the buoy communication signal according to the characteristic parameters of the time-frequency spectrum; the types of the buoy communication signal include: a first type of communication signal and a second type of communication signal; the first type of communication signal is MFSK, and the second type of communication signal includes: MAM, MPSK, MQAM; A classification module, used for classifying the first type of communication signal and the second type of communication signal respectively based on the characteristic value to determine the modulation signal of the latent buoy communication signal; The characteristic values ​​include a first characteristic value, a second characteristic value, a third characteristic value, a fourth characteristic value and a fifth characteristic value; the classification module is also used to: divide the second type of communication signal into three subtypes of MAM, MPSK and MQAM according to the first characteristic value; divide the first type of communication signal into three subtypes of 2FSK, 4FSK and 8FSK according to the third characteristic value, the fourth characteristic value and the fifth characteristic value; and classify the subtypes after the second type of communication signal is divided according to the second characteristic value.

6. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores machine executable instructions. When the computer executable instructions are called and executed by a processor, the computer executable instructions prompt the processor to execute the method according to any one of claims 1 to 4.

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