Control method and system for transmitting data through sound networking

Abstract

The invention discloses a control method and system for transmitting data through sound networking, and relates to the technical field of communication, and the method comprises the steps: initializing an underwater acoustic communication function at a digital signal processor, and entering a trigger state; in the triggering state, sending monitoring and receiving monitoring are executed in parallel; if the sending monitoring finds that a to-be-sent data packet exists in a preset sending queue, switching from a triggering state to a coding state, coding the to-be-sent data packet, converting the to-be-sent data packet into a sound wave signal, and sending the sound wave signal to an underwater acoustic channel; if the receiving monitoring detects that an effective sound signal exists in the underwater acoustic channel through the simulation trigger circuit, switching from a trigger state to a receiving state, and decoding the received sound wave signal to recover original data; after the task in the coding state or the receiving state is completed, the processing resources are released, and the triggering state is returned. A sensor data remote transmission solution which is low in cost, high in flexibility, easy to deploy and reliable in transmission can be provided for oil extraction pipeline monitoring in a complex environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a control method and system for transmitting data through sound networking. BACKGROUND

[0002] In the field of oilfield production and transportation, real-time monitoring of the operating state of oil production pipelines is an important link to ensure production safety and improve management efficiency. To achieve this goal, a large number of front-end sensors are usually deployed along the pipeline to collect key parameters such as pressure, temperature and flow rate. Effective transmission and reliable reception of data obtained by these sensors form the technical basis of the entire monitoring system. However, in current engineering practice, the transmission scheme of sensor data still faces many severe challenges.

[0003] Currently, in the oil production pipeline monitoring system, the transmission of front-end sensor data mainly relies on two types of technical paths. The first is the traditional wired transmission method. This method requires laying a dedicated communication cable along the pipeline to establish a physical connection between the sensor and the central control room. The system structure usually includes sensor nodes, communication cables and data receiving and processing equipment in the control room. Although wired connection can provide a stable data transmission channel in theory, it has significant limitations in practical application. First, the cost of purchasing, laying and long-term maintenance of dedicated cables is extremely high, especially when the pipeline network is widely distributed and crosses complex geographical environments, the construction difficulty increases dramatically, the cycle is long, resulting in heavy initial investment and subsequent operation and maintenance burden. Second, this method has serious lack of flexibility. When the pipeline needs to be expanded due to changes in production capacity, or the layout needs to be adjusted due to maintenance needs, the existing cable facilities are difficult to adapt quickly, and the rewiring work is tedious and costly, making the entire system lack the necessary scalability and difficult to support dynamic production management needs.

[0004] The second is to avoid the drawbacks of wired deployment, and the industry also tries to use some special wireless communication equipment. Although this type of scheme alleviates the wiring problem to some extent, it does not fundamentally solve the problem. The manufacturing cost of such wireless devices is usually high, and their communication performance is limited to a specific frequency band. In the complex environment commonly found in oil production pipelines, such as the presence of a large number of metal structures or complex electromagnetic interference, radio signals are easily shielded and interfered with, resulting in unstable communication links, high data transmission error rates, and unreliable communication links. In addition, many existing wireless schemes have bottlenecks in networking capabilities, making it difficult to support large-scale, high-density sensor node access and efficient collaborative management, limiting their feasibility in deploying throughout the pipeline.

[0005] In summary, whether relying on wired transmission of physical cables or existing partial wireless communication technologies, it is difficult to achieve a satisfactory balance in multiple key dimensions such as cost control, deployment flexibility, environmental adaptability, and communication reliability. SUMMARY

[0006] The embodiment of the present application provides a control method and system for transmitting data through sound networking, and aims to solve the technical problem of how to provide a low-cost, high-flexibility, easy-to-deploy and reliable front-end sensor data remote transmission and control method for monitoring oil pipelines.

[0007] In the first aspect, the embodiment of the present application provides a control method for transmitting data through sound networking, which is used for transmitting sensor data of an oil pipeline, and includes the following steps:

[0008] Initializing a digital signal processor to initialize a water acoustic communication function and enter a trigger state;

[0009] In the trigger state, sending monitoring and receiving monitoring are performed in parallel;

[0010] If the sending monitoring finds that there is a to-be-sent data packet in a preset sending queue, the trigger state is switched to an encoding state, the to-be-sent data packet is encoded and converted into an acoustic wave signal to be sent to a water acoustic channel;

[0011] If the receiving monitoring detects, through an analog trigger circuit, that there is a valid acoustic signal in the water acoustic channel, the trigger state is switched to a receiving state, and the received acoustic wave signal is decoded to recover original data;

[0012] After the task in the encoding state or the receiving state is completed, a processing resource is released and the trigger state is returned.

[0013] Further, the encoding of the to-be-sent data packet includes sequentially performing channel encoding, symbol mapping, inverse Fourier transform to generate an orthogonal frequency division multiplexing (OFDM) data block, adding a guard interval and a training sequence, and up-conversion processing.

[0014] Further, the training sequence includes a double-time-domain training sequence located before the OFDM data block, and a linear frequency modulation (LFM) sequence located at the head and tail of a group of OFDM data blocks.

[0015] Further, the decoding of the received acoustic wave signal includes:

[0016] The sampled acoustic wave signal is sequentially subjected to down-conversion, digital filtering, down-sampling, Fourier transform for OFDM demodulation, channel estimation and equalization, demapping, and channel decoding.

[0017] The channel estimation and equalization employs a symbol-based adaptive estimation technique, and multiple Turbo iterations can be performed between the equalizer and the decoder to transfer soft information.

[0018] Further, the to-be-sent data packet and the decoded original data are managed by an asynchronous queue.

[0019] The to-be-sent data packet is put into the sending queue by the application processor through inter-core communication.

[0020] The decoded original data is put into a preset receiving queue by the digital signal processor, and the application processor is notified to read by the inter-core communication.

[0021] Further, the method further comprises: performing distance measurement between network nodes based on sound signals; the network nodes comprise a ranging initiator and a ranging responder.

[0022] The distance measurement comprises: the ranging initiator sends a ranging packet and records a sending time T0, the ranging responder receives the ranging packet and records a receiving time T1, and then sends a response packet at a time T2, and the ranging initiator receives the response packet and records a receiving time T3.

[0023] According to a formula: distance = ((T3-T0)-(T2-T1))×sound speed / 2, the distance between the ranging initiator and the ranging responder is calculated.

[0024] Further, the method further comprises: performing time synchronization between the ranging initiator and the ranging responder based on a result of the distance measurement and a Doppler shift measurement.

[0025] Further, the method further comprises: dynamically switching power consumption modes according to system load and task scheduling.

[0026] The power consumption modes at least comprise: a sending mode for sending sound waves, a listening mode for receiving sound waves, and a sleep mode for shutting down at least part of circuits to reduce power consumption.

[0027] In a second aspect, an embodiment of the present application provides a control system for transmitting data through sound networking, which is used to implement the method in the first aspect, and the control system comprises:

[0028] An application processor running a general operating system, which is used to provide system control, a network protocol stack, and an external interface.

[0029] a digital signal processor coupled with the application processor, running a real-time operating system, for performing encoding and decoding of underwater acoustic data;

[0030] an inter-core communication module for enabling data exchange between the application processor and the digital signal processor;

[0031] wherein the program of the digital signal processor is configured to execute a state machine comprising a trigger state, an encoding state and a receiving state.

[0032] Further, the digital signal processor further comprises:

[0033] a signal processing algorithm module for performing orthogonal frequency division multiplexing (OFDM) modulation and demodulation, channel encoding and decoding, and channel estimation and equalization;

[0034] a transceiving queue management module for asynchronously managing data packets to be transmitted and received in a first-in-first-out manner;

[0035] a power consumption management module for controlling switching of the system between a transmitting mode, a listening mode and a sleep mode.

[0036] The embodiment of the present application provides a control method and system for transmitting data through sound networking. The method comprises the following steps: initializing a digital signal processor to have a water sound communication function and entering a trigger state; performing sending monitoring and receiving monitoring in parallel in the trigger state; if the sending monitoring finds that there is a data packet to be sent in a preset sending queue, switching from the trigger state to an encoding state, encoding the data packet to be sent and converting the data packet to be sent into a sound wave signal to be sent to a water sound channel; if the receiving monitoring detects, through an analog trigger circuit, that there is a valid sound signal in the water sound channel, switching from the trigger state to a receiving state, and decoding the received sound wave signal to recover original data; and releasing processing resources and returning to the trigger state after the task in the encoding state or the receiving state is completed. The present application effectively solves the problem of sensor data transmission in oil extraction pipeline monitoring by constructing an orderly control flow based on a state machine. The method enters the trigger state after the digital signal processor is initialized, performs sending and receiving monitoring in parallel in the trigger state, and ensures that the system can maintain the monitoring ability of two directions at the same time. When there is a data packet in the sending queue, the system immediately switches to the encoding state, concentrates resources to complete data encoding and sound wave signal sending, and when a valid sound signal is detected, the system quickly switches to the receiving state to specially perform signal decoding to recover original data. After each task is completed, the system releases resources and returns to the trigger state to form a complete working cycle. The clear state division and orderly conversion mechanism realize the optimal allocation of processing resources, avoid function conflicts and monitoring blind spots, and significantly improve the stability and reliability of the system in long-term operation. The characteristics of sound networking enable the method to avoid the high cost and low flexibility of traditional wired deployment, and provide a low-cost, high-flexibility, easy-to-deploy and reliable front sensor data remote transmission solution for oil extraction pipeline monitoring in complex environments. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0038] Figure 1 A structural block diagram of a control system for transmitting data through sound networking provided by the embodiment of the present application is provided.

[0039] Figure 2 A flowchart of a control method for transmitting data through sound networking provided by the embodiment of the present application is provided.

[0040] Figure 3 A structural diagram of a frame structure of OFDM transmission provided by the embodiment of the present application is provided. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort should fall within the scope of the present application.

[0042] It should be understood that the terms "comprising" and "including" as used in the specification and the appended claims indicate the presence of the described features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0043] It should also be understood that the terms used in the present application specification are only for the purpose of describing particular embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0044] It should be further understood that the term "and / or" as used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations thereof.

[0045] As used in the present application specification and the appended claims, the term "if" can be interpreted as meaning "when" or "once" or "in response to a determination" or "in response to detecting" depending on the context. Similarly, the phrases "if determined" or "if detected [the described condition or event]" can be interpreted to mean "once determined" or "in response to a determination" or "once detected [the described condition or event]" or "in response to detecting [the described condition or event]" depending on the context.

[0046] Referring to Figure 1 The embodiment of the present application provides a control system for transmitting data through sound networking, which is used for executing the control method for transmitting data through sound networking provided by the embodiment of the present application. The control system for transmitting data through sound networking comprises:

[0047] An application processor 10 (ARM) is used for providing system control, a network protocol stack and an external interface.

[0048] A digital signal processor 20 (DSP) is coupled with the application processor and is used for executing the encoding and decoding tasks of underwater acoustic data.

[0049] The inter-core communication module 30 is configured to realize data interaction between the application processor and the digital signal processor.

[0050] The program of the digital signal processor is configured to execute a state machine including a trigger state, an encoding state and a receiving state.

[0051] In the embodiment, the core of the system is to set the application processor and the digital signal processor as two processing units with different features, and to realize efficient interconnection by the inter-core communication module.

[0052] The application processor runs a general operating system (such as Linux), is good at processing non-real-time tasks such as complex network protocol stack, user interface and system scheduling, and serves as the "brain" and "diplomat" of the system, responsible for high-level decision-making and external interaction.

[0053] Further, the digital signal processor runs a real-time operating system (such as TI SYS / BIOS), is good at multiplication and addition operation and signal processing, and serves as the "professional translator" of the system, responsible for high real-time and high calculation encoding and decoding operation of underwater acoustic data. This division of labor makes both processors focus on their most suitable fields, thereby maximizing the overall performance.

[0054] Further, the program of the digital signal processor is configured to execute a state machine including a trigger state, an encoding state and a receiving state, which provides a deterministic and predictable execution framework for the whole underwater acoustic communication core process, ensuring that the system behavior is orderly and stable even under complex asynchronous event driving.

[0055] Further, the inter-core data transmission between the digital signal processor and the application processor adopts an inter-process communication mechanism. To simplify the data transmission process, the system encapsulates a unified user space I / O interface (UIO interface) on the bottom inter-core communication interface. The UIO interface adopts a symmetric architecture design, i.e. the same interface code is deployed on the digital signal processor side and the application processor side respectively, and the two sides constitute symmetric communication endpoints.

[0056] The UIO interface supports full-duplex communication mode, allowing data sending and receiving operations to be performed simultaneously. To realize this parallel processing capability, the digital signal processor side creates two independent tasks, one of which is dedicated to data packet sending and the other is dedicated to data packet receiving. Correspondingly, the application processor side also creates two independent threads, which respectively undertake the functions of data packet sending and receiving.

[0057] Based on the symmetric characteristic of the UIO interface, when the digital signal processor side calls a sending function, the corresponding receiving function of the application processor side will synchronously obtain the data packet; similarly, when the application processor side calls a sending function, the corresponding receiving function of the digital signal processor side will also synchronously obtain the data packet. The symmetric design ensures the efficiency and reliability of the inter-core data transmission, and provides a unified and simplified data interaction channel for the dual-core system.

[0058] Further, the digital signal processor further comprises:

[0059] a signal processing algorithm module, configured to perform orthogonal frequency division multiplexing (OFDM) modulation and demodulation, channel coding and decoding, and channel estimation and equalization;

[0060] a transceiving queue management module, configured to asynchronously manage data packets to be sent and data received in a first-in-first-out manner;

[0061] a power consumption management module, configured to control switching of the system between a sending mode, a listening mode and a sleep mode.

[0062] In a specific implementation, the signal processing algorithm module encapsulates all the underlying algorithms such as OFDM modulation and demodulation, channel coding and decoding, and channel estimation and equalization together, which enables algorithm optimization and upgrading to be concentrated in this module without the need to change other parts of the system.

[0063] Further, the transceiving queue management module is specially responsible for managing data flow in a first-in-first-out manner, and it acts as a "buffer hub" in the data pipeline, effectively decoupling the problem of mismatched processing speeds, ensuring smooth and orderly flow of data between the dual cores, which greatly enhances the stability and throughput of the system.

[0064] Further, the power consumption management module controls the switching strategy and hardware control of the system in different power consumption modes, and it acts as an "energy manager" to accurately control the power supply state of each functional unit according to the task scheduling of the system, and it is the specific executor of low power consumption effect. The three modules work together to form the cornerstone of the powerful functions of the digital signal processor.

[0065] Further, the control system for transmitting data through sound networking further comprises a file transmission module, and the file transmission module transmits files between the application processor and the digital signal processor based on the YModem protocol.

[0066] In the development and operation of underwater acoustic communication equipment, it is often necessary to transmit non-real-time files with large data volume between the application processor and the digital signal processor, such as the received signal waveform record for post-analysis, the specific acoustic waveform file for direct playback, or the update image of the digital signal processor program.

[0067] As a mature file transfer protocol, the YModem protocol has the characteristics of packet structure specification, support for 1024-byte large packet transmission, and checksum retransmission mechanism compared with simple byte stream transmission. After integrating this module, the system can reliably transmit complete files with high efficiency, effectively avoiding file damage caused by data errors or loss during transmission. For example, during debugging, engineers can upload suspicious signal waveform files collected by the digital signal processor to the application processor and then export them for analysis through the network, which is crucial for locating and solving complex channel interference problems. In addition, when upgrading or repairing the digital signal processor firmware, a new firmware file can be downloaded remotely through the application processor, and then safely and reliably transmitted to the digital signal processor using this file transfer module, realizing remote online updating and saving the trouble of opening and plugging, significantly reducing the maintenance cost and time of the equipment. This module adds an important non-real-time large data interaction dimension to the system, improving its overall functionality and practicality.

[0068] There are many communication signals in the YModem protocol transmission process, and their values and meanings are shown in Table 1:

[0069] Symbol Value Meaning SOH 0x01 128 byte data packet STX 0x02 1024 byte data packet EOT 0x04 End of transmission ACK 0x06 Acknowledge NAK 0x15 Not acknowledged CA 0x18 Call aborted C 0x43 Request data packet

[0070] Table 1. Meaning of Ymodem command bytes

[0071] Further, the digital signal processor is connected with an external SD storage card, which is used to store received acoustic waveform files during system debugging or pre-store waveform files to be directly sent. To manage the files and directories in the SD card in a structured manner, the system is provided with a file system module.

[0072] The file system module is implemented based on the FAT32 specification, and its role is to convert high-level operations on files and folders into physical block address operations on the SD card storage medium. The SD card driver itself only provides block-level read-write and erase interfaces based on physical sectors, and the file system module builds logical file management functions that meet the FAT32 standard based on this.

[0073] The logical structure of the FAT32 file system includes several key data structures, among which the core is the file allocation table and the directory entry. The file allocation table is used to record the cluster chain allocation of file data in the storage space; the data content of each file or directory is stored in continuous or discontinuous space composed of one or more clusters, and if a file or directory occupies more than one cluster, the file allocation table indicates the location of the next cluster through a linked list structure, while marking the allocation status of each cluster and bad cluster information. The directory entry is used to describe the metadata of the file or directory, and the FAT32 file system allocates a directory entry for each file or directory, which records key information including name, size, attribute, creation time, and starting cluster number of file content.

[0074] The metadata of the file system itself is recorded in the boot sector located at logical sector 0 of the storage device, which is also called the DOS boot record. The boot sector stores key parameters such as the starting position of the file system, the total capacity, the number and size of the file allocation table, and the number of sectors per cluster. In the address management mechanism of the FAT32 file system, both sector addresses and cluster addresses are used. In the file system management area, system areas such as the boot sector, file allocation table area, and root directory area are usually managed using sector addresses; while the actual data content of user files and directories is stored in the data area, which is allocated and managed in clusters.

[0075] Based on the above FAT32 specification, the file system module implements a series of file and directory operation functions, including but not limited to: mounting and unmounting storage devices, formatting devices, modifying access permissions of files or directories, renaming files or directories, obtaining file status information; supporting file opening, closing, reading, writing, file data positioning, and read-write synchronization; and supporting directory reading, creation, and deletion operations.

[0076] Please refer to Figure 2 The embodiment of the application provides a control method for transmitting data through sound networking, which is used for transmitting sensor data of a production pipe, and is applied to the system. The method comprises the following steps:

[0077] S1: initializing the underwater acoustic communication function in the digital signal processor and entering a trigger state.

[0078] In the specific implementation, at startup, the initialization of the underwater acoustic communication function in the digital signal processor is completed and the trigger state is entered, thereby establishing a stable and repeatable starting point for the entire communication process, ensuring that the system can be in a known and determined state after each startup, and laying a foundation for subsequent reliable communication behavior.

[0079] S2: in the trigger state, sending monitoring and receiving monitoring are performed in parallel.

[0080] In the specific implementation, when the system is in the trigger state, it performs the sending monitoring and the receiving monitoring in parallel, greatly improving the resource utilization efficiency and the system response capability. The parallel monitoring mechanism enables the system to maintain the monitoring capability for both directions at the same time without having to make a single choice between the sending and receiving functions. This design effectively avoids the monitoring blind area caused by function switching in the traditional system, ensuring that the system can timely capture the changing communication opportunities in the underwater acoustic channel, and creating the necessary conditions for maintaining a stable communication link in a complex underwater acoustic environment.

[0081] S3: If the sending monitoring finds that there is a data packet to be sent in the preset sending queue, switch from the trigger state to the encoding state, encode the data packet to be sent and convert it into an acoustic wave signal to be sent to the underwater acoustic channel.

[0082] In the specific implementation, if the sending monitoring finds that there is a data packet (which can be specifically sensor data) to be sent in the preset sending queue, the system can immediately switch from the trigger state to a dedicated encoding state, realizing the optimal allocation of processing resources and the specificity of task execution. When the system enters the encoding state, the digital signal processor performs the task of encoding the data packet and converting it into an acoustic wave signal, which ensures the quality and efficiency of signal generation. At the same time, the encoded acoustic wave signal is sent to the underwater acoustic channel for transmission to the preset receiving target, avoiding problems such as incomplete data sending or timing errors caused by resource competition.

[0083] In some preferred embodiments, the above step of "encoding the data packet to be sent" specifically includes the following steps: sequentially performing channel encoding, symbol mapping, inverse Fourier transform on the data packet to be sent to generate an orthogonal frequency division multiplexing (OFDM) data block, adding a guard interval and a training sequence, and up-conversion processing.

[0084] In the specific implementation, first, the data packet to be sent is channel encoded. This step constructs an encoded data block with forward error correction capability by systematically adding redundant check bits to the original data bit stream. The purpose is to enable the receiving end to detect and correct errors using these redundant information when the signal encounters noise, interference or fading during transmission in the underwater acoustic channel, thereby improving the reliability of data transmission. A typical implementation is to use a low-density parity-check code encoding algorithm.

[0085] Further, the channel encoded data block is subjected to symbol mapping. This process maps the coded binary bit sequence into modulation symbols in the complex domain according to a predetermined modulation format. Specifically, each group of bits is mapped into a complex symbol with a specific amplitude and phase, for example, using a quadrature amplitude modulation scheme, the bit sequence is mapped onto corresponding constellation points. This step converts the digital bit stream into a symbol sequence representing the transmitted waveform, preparing for subsequent frequency domain modulation.

[0086] Further, the symbol mapped parallel symbol sequence is subjected to inverse Fourier transform to generate an orthogonal frequency division multiplexing, OFDM, data block. Specifically, the complex symbols are distributed onto a number of orthogonal subcarriers, and the subcarrier symbol set in the frequency domain is transformed into a complex OFDM data block in the time domain by performing an inverse fast Fourier transform operation. This operation converts the high speed serial data stream into a number of parallel low speed subcarrier transmissions, effectively lengthening the duration of each symbol and enhancing the system's ability to combat inter-symbol interference caused by the multipath effect of the underwater acoustic channel. Specifically, referring to Figure 3 , the OFDM frame structure includes a detection preamble and a synchronization preamble, followed by the OFDM data block.

[0087] Further, a guard interval and training sequence are added. Before the generated OFDM data block, a specific sequence called guard interval is inserted. The guard interval is usually constructed by copying a portion of the samples at the end of the OFDM data block and placing them at the beginning, forming a cyclic prefix. The cyclic prefix can absorb the multipath time delay spread of the channel, ensuring that the orthogonality between subcarriers is maintained during demodulation. Meanwhile, known training sequences are inserted at specific locations in the guard interval and / or a group of OFDM data blocks. The training sequences include, but are not limited to, a two-time-domain training sequence for accurate time synchronization and channel estimation, and a linear frequency modulation sequence for signal detection and Doppler estimation. These sequences provide the necessary reference for the receiving end to perform signal detection, synchronization, channel estimation and equalization.

[0088] Further, up-conversion processing is performed. The baseband digital signal obtained by the above steps is subjected to frequency spectrum shifting by a digital up-converter to the acoustic passband frequency range specified by the underwater acoustic communication system design. Specifically, the baseband complex signal is multiplied by a carrier complex exponential signal, so that the frequency spectrum center of the signal is shifted from zero frequency to the target carrier frequency. Subsequently, the passband digital signal is converted into an analog signal by a digital-to-analog converter, and after power amplification, it is converted into a physical acoustic wave signal by a transducer and radiated into the underwater acoustic channel.

[0089] Through the above-mentioned signal processing steps performed in sequence, the data packet to be transmitted is systematically constructed into a robust physical waveform with strong anti-interference capability, high spectral efficiency and suitability for transmission in a complex underwater acoustic channel.

[0090] In some preferred embodiments, the training sequence comprises a double time-domain training sequence located before the OFDM data block, and a linear frequency modulation (LFM) sequence located at the head and tail of the group of OFDM data blocks.

[0091] In a specific implementation, a combination of a double time-domain training sequence and a grouped linear frequency modulation (LFM) sequence is adopted, which brings synergistically enhanced synchronization, channel estimation and anti-time-varying effects. The double time-domain training sequence located before each OFDM data block has a first sequence that functions as a guard interval and also as a cyclic prefix for a second sequence, which enables the second sequence to maintain its waveform structure even in a severe multipath channel, thereby being used by the receiving end for accurate channel impulse response estimation. Accurate channel estimation is a prerequisite for subsequent effective equalization and elimination of channel distortion.

[0092] Further, the insertion of a linear frequency modulation (LFM) sequence at the head and tail of the group of OFDM data blocks endows the received signal with strong time positioning and Doppler shift estimation capability. The LFM signal has sharp autocorrelation characteristics similar to radar pulse compression due to its linear variation of frequency with time, and the receiving end can extremely accurately determine the start and end time of the data group by cross-correlation operation with the known LFM sequence. This accurate time length estimation is crucial for compensating for the signal time axis stretching (i.e., Doppler effect) caused by relative motion of the transmitting and receiving platforms.

[0093] In the present embodiment, the joint use of the two training sequences collectively counteracts the challenges of underwater acoustic channel time variation and multipath from the "microscopic" (channel estimation for a single data block) and "macroscopic" (time scale estimation for the entire group of data) levels, significantly improving the synchronization accuracy and overall demodulation performance of the system in a dynamic underwater acoustic environment.

[0094] S4: If the receiving monitoring detects the presence of an effective acoustic signal in the underwater acoustic channel through the analog trigger circuit, the trigger state is switched to the receiving state, and the received acoustic wave signal is decoded to recover the original data.

[0095] In the implementation, if the monitoring and receiving detects that there is an effective acoustic signal (which can be specifically sensor data) in the underwater acoustic channel through the analog trigger circuit, the system can quickly switch from the trigger state to the receiving state, making full use of the high efficiency and real-time performance of the hardware trigger to ensure that the system can respond to the effective signal in the underwater acoustic channel in time. The time-varying characteristics of the underwater acoustic channel make the signal transmission window often fleeting. The fast state switching based on the hardware trigger can maximize the capture of effective signals and create a prerequisite for subsequent signal decoding.

[0096] In some preferred embodiments, the above step of "decoding the received acoustic signal" specifically includes the following steps: sequentially performing down-conversion, digital filtering, down-sampling, Fourier transform for OFDM demodulation, channel estimation and equalization, demapping, and channel decoding on the sampled acoustic signal; wherein the channel estimation and equalization adopts a symbol-based adaptive estimation technique, and multiple Turbo iterations can be performed between the equalizer and the decoder to transfer soft information.

[0097] In the implementation, first, the passband digital signal obtained by the analog-to-digital converter at a certain sampling rate is subjected to down-conversion processing. By mixing the received passband signal with a locally generated complex exponential signal corresponding to the carrier frequency of the transmitting end, the frequency spectrum of the signal is shifted from the target passband back to the baseband, thereby obtaining a complex baseband signal for subsequent low-pass filtering and baseband signal processing.

[0098] Further, the complex baseband signal obtained after down-conversion is subjected to digital filtering and down-sampling. This process uses a digital low-pass filter to filter out high-frequency components generated during the mixing process, as well as out-of-band noise and interference, and retains the useful signal band. Subsequently, the filtered signal is subjected to down-sampling processing, i.e., reducing the data rate of the signal according to a predetermined decimation factor. This step significantly reduces the computational load and data throughput pressure of the subsequent signal processing module while ensuring that the signal information is not distorted.

[0099] Further, Fourier transform is performed on the down-sampled time-domain baseband signal block for OFDM demodulation. Specifically, fast Fourier transform is performed on each valid OFDM symbol block after removing the guard interval, converting the time-domain signal back to the frequency domain, and recovering the frequency-domain symbols carried on each orthogonal subcarrier. This step realizes the demodulation of the OFDM signal, and decomposes the complex time-domain waveform into parallel subcarrier symbol streams.

[0100] Further, channel estimation and equalization are performed. This step further includes two sub-processes that work together:

[0101] Channel estimation: The frequency response of the underwater acoustic channel is tracked and estimated in real time by a symbol-based adaptive estimation technique, exploiting the known training sequences embedded in the transmitted signal (e.g. the double time-domain training sequence). A preferred implementation employs a modified proportional normalized least mean square (IPNLMS) algorithm, which is particularly suitable for exploiting the sparse nature of the underwater acoustic channel, thereby accelerating the convergence and improving the estimation accuracy.

[0102] Equalization: The frequency response obtained from the channel estimation is used to compensate for the distortion introduced by the channel, on the frequency-domain symbols obtained after OFDM demodulation. A typical implementation employs a minimum mean square error equalizer to suppress the amplitude fading and phase rotation introduced by the channel, and to correct for the interference between subcarriers.

[0103] Further, the equalized frequency-domain symbols are de-mapped. This process determines the binary bit likelihood information corresponding to each complex symbol, according to the symbol mapping rule employed at the transmitter (e.g. QAM constellation). Specifically, the posterior probability or log-likelihood ratio of each bit being 0 or 1 is computed, providing soft input information for the subsequent channel decoding.

[0104] Further, channel decoding is performed. This step, which is the inverse of the channel encoding, exploits the redundancy check bit relationships introduced at the transmitter, to correct the binary bit stream or soft information sequence obtained after de-mapping. When a Turbo iterative mechanism is employed, the decoding process is represented as an iterative loop:

[0105] The channel decoder decodes the soft information from the de-mapper, and outputs more reliable, error-corrected soft information; this soft information is interleaved and fed back to the equalizer as a-priori information, to guide the next round of equalization and symbol detection; the equalizer uses this a-priori information to produce updated, more accurate symbol soft information, which is de-interleaved and sent back to the channel decoder. This Turbo iterative process is repeated multiple times between the equalizer and the decoder, through the cyclic transfer and gradual refinement of soft information, continuously improving the accuracy of signal detection and decoding, and thereby achieving extremely low bit error rates under severe underwater acoustic channel conditions.

[0106] Through the above sequentially connected and iterative signal processing steps, the system is able to recover the original transmitted data from the severely contaminated received acoustic signal with high probability.

[0107] In some preferred embodiments, the channel estimation employs a modified proportional normalized least mean square (IPNLMS) algorithm.

[0108] In the implementation, the channel estimation is embodied as an improved proportionally normalized least mean square (IPNLMS) algorithm, which brings the accurate estimation effect for the unique properties of the underwater acoustic channel and faster convergence speed. Specifically, an important feature of the underwater acoustic channel is that its impulse response often has sparsity, i.e., most of the energy is concentrated in a few main propagation paths, and the responses of other paths are very weak or even zero.

[0109] The traditional LMS algorithm updates all taps with the same step size, which fails to take advantage of this sparsity. The improvement of the IPNLMS algorithm lies in that it introduces a proportional factor that can adaptively adjust the update step size of each tap (path) estimate according to the absolute value of the estimate. For the key paths with strong energy, a larger step size is given to speed up the convergence; for the non-key paths with weak or zero energy, a very small step size is given or even the update is suppressed.

[0110] This "different treatment" strategy enables the convergence energy of the algorithm to be concentrated on capturing those truly important channel components, so that more accurate and clearer channel estimation results can be obtained than the traditional algorithm under the same number of iterations. More accurate channel estimation directly means that the equalizer can more perfectly compensate for channel distortion, which brings significant improvement in overall reception performance when combined with Turbo iteration, and also improves the algorithm efficiency and saves the computing resources of the digital signal processor.

[0111] S5: After the task in the encoding state or the receiving state is completed, the processing resource is released and the trigger state is returned.

[0112] In the implementation, after the task in the encoding state or the receiving state is completed, the system completes a complete working cycle by releasing the processing resource and returning to the trigger state, realizing effective management and recycling of system resources. By regularly releasing the processing resource that is no longer needed, the system avoids the accumulation of problems such as memory leakage or resource fragmentation, which is particularly important for the oil pipeline monitoring system that needs to run continuously for a long time. Returning to the unified trigger state provides a clean initial environment for processing the next communication task, whether it is a new sending task or a receiving task, which can start processing under the same baseline conditions. This consistency greatly enhances the predictability and reliability of system behavior.

[0113] The application establishes a highly structured and self-sustaining work flow for the underwater acoustic communication system through clear state division and orderly state conversion. The conversion logic between states is clear and covers all possible communication scenarios, so that the system can reasonably handle the competition between sending and receiving tasks, avoiding resource conflicts and processing deadlocks. This order not only improves the success rate of a single communication event, but more importantly, ensures the stability and reliability of the system in long-term operation.

[0114] The application forms a complete underwater acoustic data transmission control scheme through the organic combination of the above technical steps, which can significantly improve the reliability of sensor data transmission in the oil pipeline monitoring system. At the same time, due to its characteristics based on sound networking, it avoids the high cost and low flexibility problems of traditional wired deployment, providing an effective technical approach for realizing low-cost, high-flexibility, easy-to-deploy, and reliable front-end sensor data remote transmission and control in complex environments. The advantage of this method is not only reflected in the working efficiency of a single device, but also in laying a solid technical foundation for building a large-scale and highly reliable underwater acoustic sensor network.

[0115] In some preferred embodiments, the to-be-sent data packet and the decoded and recovered original data are managed by an asynchronous queue; wherein the to-be-sent data packet is put into the sending queue by the application processor through inter-core communication; and the decoded and recovered original data is put into a preset receiving queue by the digital signal processor and notifies the application processor to read through the inter-core communication.

[0116] In specific implementation, the asynchronous queue management mechanism ingeniously solves the speed mismatch and resource competition problems between high-speed and low-speed devices and different processing units in the underwater acoustic communication system by introducing a data buffer and decoupling layer, thereby ensuring the smoothness and data integrity of the system.

[0117] Specifically, the application processor as a general-purpose computing unit generates or receives network data packets at a relatively high speed and possibly in bursts, while the underwater acoustic encoding and decoding performed by the digital signal processor and the transmission process through the physical channel are relatively slow. Without a sending queue, the sending request of the application processor may be blocked or discarded because the digital signal processor is busy processing the previous packet or is in a receiving state. The existence of the sending queue allows the application processor to immediately return after putting the to-be-sent data packet into the queue through inter-core communication, without waiting for the actual sending to be completed, realizing the asynchronization of the sending task and freeing the performance of the application processor.

[0118] Similarly, the receiving queue provides a temporary storage for the data packet demodulated by the digital signal processor, so that the digital signal processor can quickly store the data packet in the queue and then process the next signal without waiting for the application processor to respond in time. The application processor can calmly read data from the receiving queue during its scheduling period. This decoupling of production and consumption effectively smooths the data flow, prevents the high-speed end from impacting the low-speed end, and avoids the idle processing unit or data loss caused by inter-core communication waiting, so that the digital signal processor can focus on real-time signal processing, the application processor can focus on network and control, and both can work together without blocking each other, greatly improving the work efficiency and stability of the entire system.

[0119] In some preferred embodiments, the method further comprises: measuring the distance between network nodes based on the sound signal. It can be understood that the network nodes are each configured with the control system for transmitting data through sound networking according to the embodiments of the present application; the network nodes include a distance measurement initiator and a distance measurement responder; the distance measurement includes: the distance measurement initiator sending a distance measurement packet and recording a sending time T0, the distance measurement responder receiving the distance measurement packet and recording a receiving time T1, then sending a response packet at a time T2, and the distance measurement initiator receiving the response packet and recording a receiving time T3; and the distance between the distance measurement initiator and the distance measurement responder is calculated according to the formula: distance = ((T3-T0)-(T2-T1))×speed of sound / 2.

[0120] In a specific implementation, the distance measurement method based on the sound signal effectively eliminates the error caused by the internal processing delay of the device in the distance measurement process through a clever bidirectional timestamp exchange mechanism, thereby realizing high-precision distance measurement.

[0121] Specifically, the distance measurement initiator is required to record not only the time T0 of sending the distance measurement packet and the time T3 of receiving the response packet, but more importantly, the responder also needs to record the time T1 of receiving the distance measurement packet and the time T2 of sending the response packet. In the final distance calculation formula "distance = ((T3-T0)-(T2-T1))×speed of sound / 2", "(T3-T0)" represents the total time of the entire round-trip process of the signal, which includes not only the real delay of sound propagation in the medium, but also the internal processing delay (i.e. T2-T1) of the responder device. By subtracting the processing delay "(T2-T1)" from the total time, the formula cleverly eliminates the error introduced by non-propagation factors. This makes the final measurement result purely reflect the time consumed by the sound signal in the propagation between the distance measurement parties.

[0122] For example, even if the responder is slowed down due to high load, the processing delay will be accurately deducted and will not affect the final ranging accuracy. This method reduces the stringent requirements on the real-time response performance of the device, making it possible to achieve ranging accuracy equivalent to high-end devices even on nodes using low-cost processors, providing a reliable spatial location information basis for the entire network.

[0123] In some preferred embodiments, the method further comprises performing time synchronization between the ranging initiator and the ranging responder based on the results of the distance measurement and the Doppler shift measurement.

[0124] In practice, traditional clock synchronization algorithms often assume that nodes are stationary or only consider fixed propagation delays. However, in underwater environments, nodes drift with the current or move autonomously, which not only leads to dynamic changes in propagation delays but also causes shifts in received signal frequencies due to the Doppler effect.

[0125] The core of the present embodiment lies in the realization that the sum of the round-trip propagation delays is a function of the combined effects of clock skew and relative motion. High-precision distance measurement provides accurate information about the length of the propagation path, while measurement of the Doppler shift allows accurate calculation of the relative radial velocity between nodes. By multiplying the relative velocity by time, the additional path change due to relative motion during signal interaction can be calculated. By converting this path change into a delay correction, the effects of motion can be removed from the measured total time difference, allowing accurate calculation of the pure clock skew. This dynamic compensation mechanism allows the time synchronization process to adapt to node mobility, avoiding the accumulation of synchronization errors due to motion, thereby providing a unified, stable, and accurate time reference for the entire acoustic network, which is crucial for distributed monitoring applications that require coordinated sampling, time division multiple access, or data fusion.

[0126] Specifically, the specific implementation of the above-mentioned time synchronization includes:

[0127] First, based on the data obtained from the aforementioned distance measurement process, the one-way propagation delay of the signal between the ranging initiator and the ranging responder is calculated. Specifically, the calculated distance value is divided by the speed of sound in the underwater acoustic channel to derive the theoretical one-way propagation time of the signal.

[0128] Further, in the distance measurement process, a Doppler shift measurement is performed by performing a spectrum analysis on the response packet or a specific synchronization signal. The Doppler shift measurement is performed by comparing the center frequency of the received signal with the original center frequency of the transmitted signal, and calculating the frequency difference therebetween, which is the Doppler shift. Then, according to the Doppler shift value, the relative radial velocity of the ranging initiator and the ranging responder in the direction of the signal propagation path is calculated using the Doppler effect formula.

[0129] Further, the one-way propagation delay is dynamically corrected using the relative radial velocity. Since the relative motion between the nodes causes the actual propagation path length to continuously change during the entire time period of the signal interaction, the initial calculated propagation delay based on a fixed distance has an error. By multiplying the relative radial velocity by a specific time segment during the signal interaction, the additional path length change caused by the relative motion during the time segment is estimated, and the path change is converted into a corresponding propagation delay change. The initial one-way propagation delay is compensated using the delay change, thereby obtaining a more accurate corrected propagation delay reflecting the motion state of the nodes.

[0130] Further, based on the corrected propagation delay and the time stamp recorded during the distance measurement process, the clock bias between the ranging initiator and the ranging responder is calculated. Specifically, by establishing an equation set containing the corrected propagation delay, the time stamp, and the clock bias to be solved, the clock bias of the ranging initiator relative to the ranging responder is solved.

[0131] Finally, the ranging initiator and / or the ranging responder adjusts the phase and frequency of the local clock according to the calculated clock bias, to achieve the alignment of the two in the time scale. The adjustment process can be completed at one time, or as an input of a closed-loop control system, by repeatedly performing the ranging, Doppler measurement, and clock bias calculation steps, the time synchronization error is iteratively reduced and eventually eliminated, thereby achieving and maintaining high-precision time synchronization under the condition that the network nodes are relatively moving.

[0132] In some preferred embodiments, the method further comprises: dynamically switching the power consumption mode according to the system load and task scheduling; the power consumption mode at least includes: a transmission mode for transmitting acoustic wave signals, a listening mode for receiving acoustic wave signals, and a sleep mode of shutting down at least part of the circuit to reduce power consumption.

[0133] In the embodiment, the system is defined with multiple differentiated energy consumption levels, and can intelligently switch according to actual task requirements, thereby greatly prolonging the continuous working time of the device in the field or in the environment without stable power supply, while ensuring the communication function. The system defines at least a sending mode, a listening mode and a sleep mode. In the sending mode, the power amplifier and other high-power circuits are turned on to ensure the transmission power and communication distance of the signal. In the listening mode without sending but needing to maintain network connection, the system can turn off the power amplifier and other unnecessary high-power units, and only maintain the working of the receiving circuit, at which time the power consumption is significantly reduced, but the device can still respond to the call from the network at any time. When there is no communication task for a long time, the system can enter a deeper sleep mode, at which time most of the peripherals and even the core circuit of the digital signal processor and the application processor can be turned off or clock-gated, and only the most basic analog trigger circuit and memory refresh function are retained. Once the analog trigger circuit detects a valid wake-up signal (such as a specific acoustic preamble), the system can be quickly woken up to a full-function working state. This on-demand power supply strategy avoids continuous waste of energy, so that the working life of the device is no longer limited by the peak power consumption, but by the average power consumption and the total capacity of the battery, which has extremely important practical significance for the sensor network deployed in remote oil pipelines that need to be continuously monitored for several years or even longer.

[0134] In the embodiment, the dynamic switching power consumption mode is implemented as follows:

[0135] The system predefines at least three power consumption modes, namely a sending mode, a listening mode and a sleep mode. During system operation, a central power consumption management module dynamically determines and executes the switching between modes according to the predetermined task scheduling strategy and the real-time system load condition.

[0136] Further, when it is determined that there is a data packet to be sent for transmission through the underwater acoustic channel, the power consumption management module controls the system to switch from the current mode to the sending mode. In this mode, the module at least performs the following operations: turning on the power supply circuit of the power amplifier chip to provide the necessary working bias voltage and current for the power amplifier to ensure that the acoustic signal can be radiated with sufficient power; at the same time, maintaining the normal working voltage and clock frequency of the digital signal processor, the application processor and all peripheral circuits related to signal generation and transmission, thereby ensuring the complete execution of the coding and signal modulation tasks.

[0137] When there is no immediate sending task but the system needs to keep the ability of continuous listening to the underwater acoustic channel, the power management module controls the system to enter the listening mode. In this mode, the module at least performs the following operations: the power supply circuit of the power amplifier chip is turned off to eliminate its static power consumption; at the same time, the analog trigger circuit, the signal receiving link, the digital signal processor core and the relevant modules in the application processor responsible for receiving and processing tasks are kept in normal working state. This configuration enables the system to continuously detect whether there is a valid synchronization preamble or data packet in the underwater acoustic channel, and prepares for the subsequent possible triggering of the receiving state processing flow.

[0138] When the system does not monitor any sending task and underwater acoustic trigger event within a predetermined time period, the power management module controls the system to enter the sleep mode. In this mode, more in-depth power consumption control operations are performed, which at least include: turning off the power supply and clock signal of unnecessary peripheral devices in the digital signal processor and the application processor; saving the current working state and register content of the digital signal processor and the application processor to the low-power self-refresh memory; then, placing the main functional units of the system in a standby state with the lowest energy supply. At this time, only the analog trigger circuit, the interrupt controller for responding to wake-up events and the basic circuit for maintaining memory data in the entire system are in active state. When the analog trigger circuit detects an underwater acoustic signal meeting the preset characteristics, it generates a hardware interrupt signal, which triggers the system to recover from the sleep mode; the power management module immediately reopens the power supply and clock domain that are turned off, and recovers the previous state of the processor from the self-refresh memory, so that the system quickly returns to the listening mode or directly enters the receiving state, thereby achieving the balance between power consumption saving and fast response ability.

[0139] The switching of the power consumption mode is a closed-loop dynamic process, which is continuously monitored by the power management module for the system task queue, event trigger state and timer timeout signal, and according to these input parameters, the state transition logic is automatically and seamlessly migrated between different power consumption modes, thereby minimizing the overall energy consumption of the system while ensuring the real-time performance of the communication function.

[0140] The embodiment of the present application provides a control method for transmitting data through sound networking, comprising: initializing a digital signal processor to have a sound communication function and entering a trigger state; performing sending monitoring and receiving monitoring in parallel in the trigger state; if the sending monitoring finds that there is a data packet to be sent in a preset sending queue, switching from the trigger state to an encoding state, encoding the data packet to be sent and converting the data packet to be sent into a sound wave signal to send to a sound channel; if the receiving monitoring detects that there is a valid sound signal in the sound channel through an analog trigger circuit, switching from the trigger state to a receiving state, and decoding the received sound wave signal to recover original data; after the task in the encoding state or the receiving state is completed, releasing a processing resource and returning to the trigger state. The present application effectively solves the problem of sensor data transmission in oil extraction pipeline monitoring by constructing an ordered control flow based on a state machine. The method first enters a trigger state after the digital signal processor is initialized, performs sending and receiving monitoring in parallel in the state, and ensures that the system can maintain the monitoring ability of two directions at the same time. When there is a data packet in the sending queue, the system immediately switches to the encoding state, concentrates resources to complete data encoding and sound wave signal sending; when a valid sound signal is detected, the system quickly switches to the receiving state and specially performs signal decoding to recover the original data. After each task is completed, the system releases the resource and returns to the trigger state, forming a complete working cycle. The clear state division and ordered conversion mechanism realize the optimal allocation of the processing resource, avoid function conflicts and monitoring blind areas, and significantly improve the stability and reliability of the system in long-term operation. Based on the characteristics of sound networking, the method avoids the high cost and low flexibility of traditional wired deployment, and provides a low-cost, high-flexibility, easy-to-deploy and reliable front-end sensor data remote transmission solution for oil extraction pipeline monitoring in complex environments.

[0141] Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in the above description in general terms. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0142] In several embodiments provided by the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. For example, the described apparatus embodiments are merely schematic. For example, the division of the units is merely a logical function division. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In a possible implementation process, the steps of the described method can be performed in a different order, or can be omitted, or can be combined into another process, or can be implemented with other technical solutions.

[0143] The steps in the method embodiments of the present application can be adjusted, combined and deleted in sequence according to actual needs. The units in the apparatus embodiments of the present application can be combined, divided and deleted according to actual needs. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0144] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a terminal or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application.

[0145] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0146] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, these modifications and variations also belong to the scope of the claims of the present application and their equivalent technologies, and the present application is intended to include these modifications and variations.

[0147] The above description is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A control method for transmitting data through sound networking, the method comprising: receiving a sound signal from a first device; and transmitting a data signal to the first device in response to the sound signal. A method for transmitting sensor data of a production tubing, comprising: initializing a water acoustic communication function in a digital signal processor and entering a trigger state; in the trigger state, performing sending monitoring and receiving monitoring in parallel; if the sending monitoring finds that there is a data packet to be sent in a preset sending queue, switching from the trigger state to an encoding state, encoding the data packet to be sent and converting it into an acoustic signal to be sent to a water acoustic channel; if the receiving monitoring detects, through an analog trigger circuit, that there is a valid acoustic signal in the water acoustic channel, switching from the trigger state to a receiving state, and decoding the received acoustic signal to recover original data; after the task in the encoding state or the receiving state is completed, releasing processing resources and returning to the trigger state.

2. The control method for transmitting data through sound networking according to claim 1, wherein, The encoding of the data packet to be sent comprises sequentially performing channel coding, symbol mapping, inverse Fourier transform to generate an orthogonal frequency division multiplexing (OFDM) data block, adding a guard interval and a training sequence, and up-conversion processing.

3. The control method of claim 2, wherein, The training sequence comprises a double-time-domain training sequence located before the OFDM data block and a linear frequency modulation (LFM) sequence located at the head and tail of a group of OFDM data blocks.

4. The control method for transmitting data through sound networking according to claim 1, wherein, The decoding of the received acoustic signal comprises: sequentially performing down-conversion, digital filtering, down-sampling, Fourier transform for OFDM demodulation, channel estimation and equalization, demapping, and channel decoding on the sampled acoustic signal; wherein the channel estimation and equalization adopt a symbol-based adaptive estimation technique, and multiple Turbo iterations can be performed between an equalizer and a decoder to transfer soft information.

5. The control method for transmitting data through sound networking according to claim 1, wherein, The data packet to be sent and the original data recovered by decoding are managed through an asynchronous queue; wherein the data packet to be sent is put into the sending queue by an application processor through inter-core communication; the original data recovered by decoding is put into a preset receiving queue by the digital signal processor, and the application processor is notified to read through the inter-core communication.

6. The control method for transmitting data through sound networking according to claim 1, wherein, The method further comprises measuring the distance between network nodes based on acoustic signals; the network nodes include a ranging initiator and a ranging responder; the distance measurement comprises: the ranging initiator sending a ranging packet and recording the sending time T0, the ranging responder receiving the ranging packet and recording the receiving time T1, and then sending a response packet at time T2, the ranging initiator receiving the response packet and recording the receiving time T3; the distance between the ranging initiator and the ranging responder is calculated according to the formula: distance = ((T3-T0)-(T2-T1))×speed of sound / 2.

7. The control method of claim 6, wherein, The method further comprises performing time synchronization between the ranging initiator and the ranging responder based on the results of the distance measurement and Doppler shift measurement.

8. The control method for transmitting data through sound networking according to claim 1, wherein, The method further comprises dynamically switching power consumption modes according to system load and task scheduling; the power consumption modes at least include a sending mode for sending acoustic signals, a listening mode for receiving acoustic signals, and a sleep mode for shutting down at least part of the circuit to reduce power consumption.

9. A control system for transmitting data through a sound mesh network, characterized by, A control system for implementing the method of any one of claims 1 to 8, comprising: an application processor running a general operating system for providing system control, network protocol stack and external interface; a digital signal processor coupled with the application processor running a real-time operating system for performing encoding and decoding of underwater acoustic data; an inter-core communication module for enabling data exchange between the application processor and the digital signal processor; wherein the program of the digital signal processor is configured to execute a state machine comprising a trigger state, an encoding state and a receiving state.

10. The control system for transmitting data through acoustic networking of claim 9, wherein: the digital signal processor further comprises: a signal processing algorithm module for performing orthogonal frequency division multiplexing (OFDM) modulation and demodulation, channel encoding and decoding, and channel estimation and equalization; a transceiving queue management module for asynchronously managing data packets to be transmitted and received in a first-in-first-out manner; and a power consumption management module for controlling switching of the system between a transmitting mode, a listening mode and a sleep mode.

Images