Underwater acoustic imaging shipborne information processing and display control system

Abstract

The invention provides an underwater acoustic imaging shipborne information processing and display control system, and relates to the technical field of underwater acoustic imaging, the underwater acoustic imaging shipborne information processing and display control system comprises a core control unit, an acoustic emission unit, a data acquisition unit, an environment perception auxiliary unit and a positioning unit, the super-resolution imaging signal generator is connected with the two power amplifier units through sixteen channels, each power amplifier unit is provided with eight channels, and each power amplifier unit is connected with eight transducers. According to the invention, through an environment adaptive algorithm and a mechanical-electronic cooperative control mechanism, the problems of poor environment adaptability, serious beam defocusing and weak fault recovery capability of a traditional fixed array underwater acoustic imaging system in a complex water area are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater acoustic imaging, and in particular to an underwater acoustic imaging shipborne information processing and display control system. Background Art

[0002] Shipborne hydroacoustic imaging is a technology that leverages the propagation characteristics of sound waves in water to perform high-resolution detection and imaging of underwater environments or targets using a vessel's onboard acoustic system. Its core approach involves transmitting acoustic signals through a transducer array, receiving reflected waves, and then combining multi-source data for signal processing and beamforming to generate visual images of underwater terrain, targets, or structures. It is widely used in marine resource exploration, shipwreck recovery, underwater pipeline monitoring, and military target identification.

[0003] Existing technologies mostly rely on single electronic beamforming or static array design, which cannot dynamically correct sound velocity gradients. For example, salinity jump layers lead to a ±5% sound velocity deviation, array element spacing and water depth mismatch, causing grating lobe interference, and a sidelobe suppression ratio of only -15dB. When a ship passes through special waters, such as the intersection of fresh water and seawater, or when the water turbidity is uneven, the ship-borne underwater acoustic imaging effect is reduced. Summary of the Invention

[0004] The purpose of the present invention is to address the shortcomings of the prior art. By dynamically adjusting the physical array of the transducer, performing real-time sound velocity correction, and performing electronic-mechanical collaborative beamforming, the present invention significantly overcomes the imaging blur and positioning deviation problems of fixed array systems in complex waters caused by sudden changes in sound velocity gradients and interference from suspended matter. At the same time, a multi-level fault-tolerant mechanism is introduced to ensure continuous operation capabilities under extreme conditions, ultimately achieving stable detection effects in turbid waters.

[0005] In order to achieve the above-mentioned object, the present invention adopts the following technical solution: an underwater acoustic imaging shipborne information processing and display control system, comprising:

[0006] A core control unit, comprising a command terminal and a phased array control host computer;

[0007] An acoustic emission unit, comprising a frequency division imaging signal generator, a movable power amplifier track module, and a phased array sound source;

[0008] A data acquisition unit, comprising a four-channel acquisition unit and a hydrophone module;

[0009] An environmental perception auxiliary unit, comprising a multi-parameter water quality sensor and an acoustic detection acquisition unit;

[0010] A positioning unit, comprising a GPS module and an inertial navigation module;

[0011] The movable power amplifier track module includes a movable track, a track servo controller, a track motor driver, and an elevation motor driver. The movable track is used to install the transducer array on the hull. The track servo controller is connected to the track motor driver and the elevation motor driver by signal.

[0012] The phased array sound source includes a power amplifier unit and a transducer array, wherein the transducer array includes sixteen transducers, and the transducers receive electrical signals from the power amplifier unit;

[0013] The accusation terminal is connected to the super-resolution imaging signal generator via a 10 Gigabit network, and the super-resolution imaging signal generator is connected to two power amplifier units via sixteen channels, each of which is allocated eight channels, and each of which is connected to eight transducers, and each of which is connected to one channel.

[0014] The command terminal is connected to the phased array control host computer via a 10 Gigabit network, and the phased array control host computer is connected to the hydrophone and the four-channel acquisition unit via two Gigabit networks respectively;

[0015] The control terminal is connected to the track servo controller via a shielded twisted pair cable, and the track servo controller is connected to the track motor driver and the elevation motor driver via a CAN bus.

[0016] The accusation terminal is connected to a digital oscilloscope via a USB 3.0 channel, and the probe of the digital oscilloscope is connected to the hydrophone;

[0017] The accusation terminal is connected to the data storage server via an optical fiber, and the data storage server is connected to the acoustic detection acquisition unit and the multi-parameter water quality sensor data via a SAS interface;

[0018] The accusation terminal is connected to the GPS module via RS232, and the accusation terminal is connected to the inertial navigation module via a 10 Gigabit network.

[0019] As a preferred embodiment, the command terminal is equipped with an environment adaptive algorithm for multi-source data fusion processing, global task scheduling and human-computer interaction interface rendering; the phased array control host computer receives hydrophone data in real time, calculates the sound source channel delay parameters and controls the signal generator and power amplifier unit; the super-resolution imaging signal generator is used to generate frequency-adjustable / phase-modulated transmission signals and receive the delay parameters of the phased array control host computer and output them in different channels; the movable power amplifier track module is used to adjust the array element spacing of the phased array sound source according to changes in water quality and adjust the array pitch of the phased array sound source to adapt to different water depths. elevation angle; the transducer array is used to convert electrical signals into sound waves, and the spatial layout of the transducer array can be changed when the movable power amplifier track module receives mechanical adjustment instructions; the four-channel acquisition unit is used to synchronously acquire transponder signals and transmit time difference data to the core control unit in real time; the hydrophone module is used to receive reflected sound wave signals and provide original acoustic data for imaging; the multi-parameter water quality sensor is used to provide real-time feedback of water environment data and trigger the update of adaptive algorithm parameters; the acoustic detection acquisition unit is used to monitor the direct wave of the phased array sound source and provide beam pointing calibration data.

[0020] As a preferred embodiment, the environment adaptive adjustment algorithm is used to optimize the formation of the phased array sound source according to the detected water quality data, and specifically includes the following steps:

[0021] S1, first perform environmental perception and parameter calculation;

[0022] S2, then mechanically and dynamically adjust the movable amplifier track module;

[0023] S3. Performing closed-loop control of the acoustic system based on the adjusted phased array sound source formation;

[0024] S4. Design a fault-tolerant mechanism.

[0025] As a preferred embodiment, in step S1, the specific process of environment perception and parameter calculation is as follows:

[0026] S1.1. First, collect environmental data: use a multi-parameter water quality sensor to obtain the water area's sound velocity, salinity, turbidity, and water temperature. Then, use the inertial navigation module to obtain the AUV's attitude data. Finally, use the hydrophone module to collect the ambient noise background spectrum.

[0027] S1.2. Perform the sound velocity compensation calculation: The sound velocity compensation calculation obtains the correction coefficient. The specific steps are as follows:

[0028] Using Leroy's correction formula:

[0029] c=1449.2+4.6T-0.055T 2+1.34(S-35)+0.016D+0.07(NTU);

[0030] The calculation process is as follows: when temperature T = 15°C, salinity S = 34.5‰, depth D = 200m, and turbidity NTU = 8, c = 1481.6m / s;

[0031] Comparing the default value c0 = 1500m / s, the correction factor is generated:

[0032] k c =c / c0=0.9877;

[0033] S1.3. Finally, formulate the transducer array formation optimization decision: formulate the transducer array formation adjustment plan based on the environmental perception data, system hardware limitations and acoustic performance.

[0034] As a preferred embodiment, in step S2, during the control process of the position of the phased array sound source on the movable power amplifier track module, the track servo controller receives an adjustment instruction, and then controls the start and stop of the track motor driver and the elevation motor driver to adjust the position of the phased array sound source unit installed on the track.

[0035] As a preferred embodiment, in step S3, the specific steps of acoustic closed-loop control are:

[0036] S3.1, delay parameter generation;

[0037] S3.2. Dynamic verification.

[0038] As a preferred implementation, in step S4, in the fault tolerance mechanism design, corresponding countermeasures are formulated according to the fault type:

[0039] 1) When the multi-parameter water quality sensor fails, historical data interpolation is enabled;

[0040] 2) When the track of the movable amplifier track module is stuck, switch to the electronic beamforming mode;

[0041] 3) When the network is interrupted, data is cached locally for ten minutes and then uploaded after the network is restored.

[0042] As a preferred implementation, in step 3.1, the specific process of generating the delay parameter is as follows:

[0043] S3.1.1. Data Input: Set the spatial coordinates of the transducers in the transducer array. The origin of the coordinate system is the geometric center of the transducer array. The X-axis of the coordinate system is along the longitudinal direction of the hull, and the Y-axis of the coordinate system is along the transverse direction of the hull. The transducer coordinates are set to (xi, yi), where i = (1, 2, 3, ..., 16). Set the angle of the transducer orientation relative to the normal direction of the transducer array to θ. Set the distance between the transducer array and the phased array sound source target to R. Set the sound speed to c. Then obtain the actual transducer spacing after the transducer position adjustment.

[0044] S3.1.2. Calculate the relative path difference: For the i-th transducer, its path difference relative to the array center is: Δd i =x i *cosθ+y i *sinθ;

[0045] S3.1.3. Calculate the theoretical time delay parameter: Convert the path difference of the transducer relative to the array center into a time difference: τ i =Δd i / c;

[0046] S3.1.4, Delay Quantization and Alignment:

[0047] The delay quantification formula is: τ quantized =round(τ i / 1ns)*1ns;

[0048] The calculation steps for inter-channel synchronization alignment are:

[0049] First find the maximum delay τ max =max(τ1,τ2,...,τ N ), the maximum value of N is 16;

[0050] So the relative delay of each channel is: Δτ i =τ max -τ i ;

[0051] S3.1.5. Generate a delay table: The table content includes the channel number and delay parameter value.

[0052] As a preferred embodiment, in step 3.2, the specific steps of dynamic verification are:

[0053] S3.2.1. Preparation: First, set the parameters of the super-resolution imaging signal generator, then calibrate the power amplifier unit to the rated power. Then, connect the digital oscilloscope to the hydrophone probe and set the trigger mode to rising edge trigger. At the same time, collect the static water background noise and test the initial sound velocity c0.

[0054] S3.2.2. Transmission triggering and data acquisition: The command terminal sends a single pulse signal to the super-resolution imaging signal generator. Each channel of the phased array acoustic source then transmits the signal in a time-sharing manner according to a preset delay table. The four-channel acquisition unit then synchronously collects the direct wave signal returned by the transponder, acquires the target reflected wave signal through the hydrophone module, and uses an oscilloscope to obtain the time-domain waveform of the sound pressure of the hydrophone module.

[0055] S3.2.3. Delay synchronization verification: Use an oscilloscope to measure the trigger time difference of each channel, and determine the delay error value between channels based on the water environment;

[0056] S3.2.4. Beam focusing effect verification: First calculate the main lobe amplitude and the ratio of the first side lobe to the main lobe amplitude. The verification formula is: Side lobe suppression ratio = 20log 10 (A side / A main ), where Amain is the main lobe peak amplitude, and Aside is the maximum side lobe peak amplitude;

[0057] S3.2.5, Signal Integrity Verification: Check that there is no distortion within the transmitted signal bandwidth and that harmonic distortion is ≤-40dBc, indicating that the spectrum is complete; perform autocorrelation analysis on the Costas coded signal, and if the main-to-sidelobe ratio is ≥13dB, the coding is verified;

[0058] S3.2.6. Verification of dynamic environmental adaptability: Trigger the sound velocity correction by rapidly injecting salinity change data; and verify the transmission power compensation under turbid water scene changes by injecting high turbidity water into the experimental chamber.

[0059] Compared with the prior art, the advantages and positive effects of the present invention are:

[0060] The present invention solves the problems of poor environmental adaptability, severe beam defocusing, and weak fault recovery capability of traditional fixed-array underwater acoustic imaging systems in complex waters through an environmental adaptive algorithm and a mechanical-electronic collaborative control mechanism. In addition, the present invention improves the main lobe energy concentration through the collaborative optimization of real-time sound velocity compensation of the Leroy model, X / Y-axis mechanical adjustment, and electronic delay control. At the same time, the system availability is improved through hardware redundancy and algorithm degradation design, significantly enhancing the imaging resolution and robustness in extreme scenarios such as turbid waters and salinity mutations. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 The present invention proposes a hardware architecture diagram of an underwater acoustic imaging ship-borne information processing and display control system;

[0062] Figure 2 The present invention proposes a module schematic diagram of an underwater acoustic imaging ship-borne information processing and display control system;

[0063] Figure 3 The present invention proposes a schematic diagram of the arrangement of a movable power amplifier track module and transducer array of an underwater acoustic imaging ship-borne information processing and display and control system. DETAILED DESCRIPTION

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0065] Example 1

[0066] like Figure 1-3 As shown, the present invention provides a technical solution: an underwater acoustic imaging shipborne information processing and display control system, comprising:

[0067] A core control unit, comprising a command terminal and a phased array control host computer;

[0068] An acoustic emission unit, comprising a frequency division imaging signal generator, a movable power amplifier track module, and a phased array sound source;

[0069] A data acquisition unit, comprising a four-channel acquisition unit and a hydrophone module;

[0070] An environmental perception auxiliary unit, comprising a multi-parameter water quality sensor and an acoustic detection acquisition unit;

[0071] A positioning unit, comprising a GPS module and an inertial navigation module;

[0072] a data storage server, wherein the data storage server receives data from the environment perception auxiliary unit;

[0073] Among them, the movable power amplifier track module includes a movable track, a track servo controller, a track motor driver, and an elevation motor driver. The movable track is used to install the transducer array on the hull. The track servo controller is signal-connected to the track motor driver and the elevation motor driver. The movable power amplifier track module installs the transducer array through the movable track, and the track servo controller drives the X / Y axis motor to dynamically adjust the horizontal spacing and vertical pitch angle of the transducers, thereby adapting to the influence of different water depths and water quality conditions on acoustic propagation, and optimizing the physical layout of the array to enhance beam focusing performance. The phased array sound source includes a power amplifier unit and a transducer array. The transducer array includes sixteen transducers. The transducers receive electrical signals from the power amplifier unit. The phased array sound source drives sixteen transducers after amplifying the electrical signals by the power amplifier unit, and generates directional sound waves through electro-acoustic conversion. The mechanical adjustability of the transducer array works in synergy with the electronic delay control to achieve adaptive adjustment of the sound wave radiation direction and energy, ultimately improving the resolution and environmental adaptability of underwater imaging.

[0074] Furthermore, the command terminal is connected to the super-resolution imaging signal generator through a 10 Gigabit network, and the super-resolution imaging signal generator is connected to two power amplifier units through sixteen channels. Each power amplifier unit is allocated eight channels, and each power amplifier unit is connected to eight transducers. Each transducer is connected to one channel. The command terminal serves as the core hub of the system, and sends high-precision acoustic parameters to the super-resolution imaging signal generator through the 10 Gigabit network, and controls it to divide the 16-channel signal into two groups to drive the two power amplifier units, so as to achieve precise matching of electrical signal power amplification and transducer; the command terminal is connected to the phased array control host computer through the 10 Gigabit network, and the phased array control host computer is connected to the hydrophone and the four-channel acquisition unit respectively through two Gigabit networks, and is connected to the phased array control host computer through another 10 Gigabit network, and obtains the hydrophone acoustic data and the time difference information of the four-channel acquisition in real time through the Gigabit network to complete beam synthesis and feedback calibration; the command terminal is connected to the track servo controller through a shielded twisted pair cable, and the track servo controller is connected to the track servo controller through CA The N vertical lines are respectively connected to the track motor driver and the elevation motor driver. The track servo control adopts a combination of shielded twisted pair and CAN bus to achieve micron-level positioning of the X / Y axis motor; the command terminal is connected to the digital oscilloscope through the USB3.0 channel, and the probe of the digital oscilloscope is connected to the hydrophone. The USB3.0 is directly connected to the digital oscilloscope to monitor the hydrophone sound pressure waveform in real time to verify the signal integrity; the command terminal is connected to the data storage server through optical fiber, and the data storage server is connected to the acoustic detection acquisition unit and the multi-parameter water quality sensor data through the SAS interface. The optical fiber is connected to the data storage server to centrally manage the acoustic detection and water quality sensor data; the command terminal is connected to the GPS module through RS232, and the command terminal is connected to the inertial navigation module through the 10 Gigabit network. The RS232 and GPS module are docked to obtain absolute positioning, and the 10 Gigabit network synchronizes the inertial navigation attitude data, and finally a closed-loop control system of multi-modal data fusion is constructed to ensure the spatiotemporal consistency and environmental adaptability of acoustic imaging;

[0075] Furthermore, the command terminal is equipped with an environment-adaptive algorithm for multi-source data fusion processing, global task scheduling and human-computer interaction interface rendering; the phased array control host computer receives hydrophone data in real time, calculates the sound source channel delay parameters and controls the signal generator and power amplifier unit; the super-resolution imaging signal generator is used to generate frequency-adjustable / phase-modulated transmission signals and receive the delay parameters of the phased array control host computer and output them in different channels. The command terminal integrates multi-source data through the environment-adaptive algorithm to achieve global optimization decision-making, drives the phased array control host computer to analyze the hydrophone reflection signal in real time and calculate the sound source channel delay parameters, synchronously controls the super-resolution imaging signal generator to generate frequency-modulated / phase-modulated coding signals, and drives the transducer array to emit directional sound waves in different channels through the power amplifier unit; the movable power amplifier track module is used to adjust the array element spacing of the phased array sound source according to changes in water quality and adjust the array pitch angle of the phased array sound source to adapt to different water depths; the transducer array is used to convert electrical signals into sound waves and can be moved on the movable power amplifier track The module changes the spatial layout of the transducer array when receiving mechanical adjustment instructions. The movable power amplifier track module dynamically adjusts the transducer spacing and pitch angle according to water quality parameters, and constructs a sound field propagation model by combining the transponder time difference data synchronously captured by the four-channel acquisition unit and the original acoustic information provided by the hydrophone; the four-channel acquisition unit is used to synchronously acquire transponder signals and transmit time difference data to the core control unit in real time; the hydrophone module is used to receive reflected sound wave signals and provide original acoustic data for imaging; the multi-parameter water quality sensor is used to provide real-time feedback of water environment data and trigger adaptive algorithm parameter updates; the acoustic detection acquisition unit is used to monitor the direct wave of the phased array sound source and provide beam pointing calibration data. The multi-parameter water quality sensor triggers the algorithm parameter update in real time, and the acoustic detection acquisition unit calibrates the beam pointing through direct wave monitoring, forming an "environmental perception-mechanical adjustment-electronic control-data feedback" closed loop, and ultimately achieving high-resolution adaptive acoustic imaging and target positioning in complex waters.

[0076] In this embodiment, the present invention, based on phased array acoustic technology, achieves high-resolution detection and imaging of underwater targets by coordinating acoustic emission, data acquisition, and environmental perception modules through a command terminal. A super-resolution imaging signal generator generates frequency- and phase-modulated acoustic signals, which are then driven by a power amplifier unit to form a dynamically controllable beam. After receiving the reflected signals, the hydrophone array, combined with data from a multi-parameter water quality sensor and a positioning unit, uses an environmentally adaptive algorithm to calculate channel delay parameters in real time, dynamically adjusting the array element spacing and pitch angle to optimize focusing.

[0077] The command and control terminal of the present invention integrates acoustic, navigation and environmental data, dispatches a signal processing cluster to complete motion compensation, super-resolution imaging and target recognition, and displays three-dimensional acoustic images and track information in real time through a display and control interface;

[0078] The present invention can achieve ultra-high imaging resolution in complex waters, such as the intersection of fresh and salt water. Through the adaptive sound speed changes of the movable track system and the real-time feedback mechanism, the beam tracking delay is greatly compressed, effectively suppressing the acoustic attenuation error caused by sudden changes in water quality, and significantly improving the underwater target detection accuracy and system environmental adaptability.

[0079] Example 2

[0080] like Figure 1-3 As shown, based on the underwater acoustic imaging shipborne information processing and display control system proposed in Example 1, the environment adaptive adjustment algorithm is used to optimize the formation of the phased array sound source according to the detected water quality data, and specifically includes the following steps:

[0081] S1. First, perform environmental perception and parameter calculation. The specific process of environmental perception and parameter calculation is as follows:

[0082] S1.1. First, collect environmental data: use a multi-parameter water quality sensor to obtain the water area's sound velocity, salinity, turbidity, and water temperature. Then, use the inertial navigation module to obtain the AUV's attitude data. Finally, use the hydrophone module to collect the ambient noise background spectrum.

[0083] Environmental data acquisition uses a multi-parameter water quality sensor to obtain real-time water sound velocity, salinity, turbidity, and water temperature. This data is combined with the AUV's attitude data from the inertial navigation module and the ambient noise spectrum collected by the hydrophone module to construct a dynamic model of the sound field propagation characteristics. The sound velocity parameter is directly used to calculate the sound source delay, salinity and turbidity data are correlated with the sound wave attenuation coefficient, and water temperature changes affect transducer efficiency. The inertial navigation attitude data compensates for beam pointing deviations caused by hull motion, while the ambient noise spectrum suppresses background interference through an adaptive filtering algorithm. Ultimately, this provides environmental baseline parameters for acoustic imaging and triggers mechanical adjustments to the transducer array and updates to the electronic beamforming parameters, forming a full-chain closed-loop feedback loop from environmental perception to acoustic control, significantly improving imaging signal-to-noise ratio and target resolution in complex waters.

[0084] S1.2. Perform the sound velocity compensation calculation: The sound velocity compensation calculation obtains the correction coefficient. The specific steps are as follows:

[0085] Using Leroy's correction formula:

[0086] c=1449.2+4.6T-0.055T 2 +1.34(S-35)+0.016D+0.07(NTU);

[0087] The calculation process is as follows: when temperature T = 15°C, salinity S = 34.5‰, depth D = 200m, and turbidity NTU = 8, c = 1481.6m / s;

[0088] Comparing the default value c0 = 1500m / s, the correction factor is generated:

[0089] kc=c / c0=0.9877;

[0090] The sound velocity compensation calculation is based on the Leroy correction formula. It dynamically calculates the actual sound velocity value by integrating four environmental parameters: temperature (T), salinity (S), depth (D), and turbidity (NTU). It then compares it with the system default sound velocity c0 = 1500m / s to generate a correction coefficient kc = 0.9877. Its core principle is to quantify the impact of environmental factors on the propagation speed of sound waves and correct the delay parameters and beam focusing model. Its function is to eliminate the sound velocity deviation caused by water temperature stratification, salinity changes, and suspended particles, ensure the physical authenticity of the transducer channel delay calculation, thereby improving the geometric accuracy of acoustic imaging and target positioning accuracy, while providing key acoustic environmental parameter input for subsequent adaptive algorithms.

[0091] S1.3. Finally, formulate a transducer array formation optimization decision: formulate a transducer array formation adjustment plan based on environmental perception data, system hardware limitations, and acoustic performance;

[0092] Transducer array formation optimization decisions are based on environmental perception data, system hardware constraints, and acoustic performance indicators. A physical formation adjustment plan is generated through multi-objective optimization algorithms, such as genetic algorithms or convex optimization. The array element spacing is dynamically adjusted based on the measured sound speed, and the array pitch angle is adjusted according to changes in water depth to optimize the acoustic wave coverage range. At the same time, the array element excitation weights are designed in conjunction with the maximum output power limit of the power amplifier unit to achieve optimal beam focusing and energy efficiency within the mechanically adjustable range. This approach aims to overcome the environmental adaptability bottleneck of fixed arrays and, through a collaborative strategy of "mechanical deformation + electronic shaping," address problems such as sudden changes in sound speed gradients and multipath interference in complex waters. Ultimately, the system achieves a dynamic balance between detection range, resolution, and power consumption, significantly improving the robustness and scene generalization capabilities of underwater imaging.

[0093] S2. The movable power amplifier track module is then mechanically and dynamically adjusted. During the control process of the position of the phased array sound source on the movable power amplifier track module, the track servo controller receives the adjustment instruction and then controls the start and stop of the track motor driver and the elevation motor driver to adjust the position of the phased array sound source unit installed on the track;

[0094] The mechanical dynamic adjustment of the movable power amplifier track module receives environmental adaptive algorithm instructions through the track servo controller, driving the track motor driver and elevation motor driver to adjust the spatial position of the phased array sound source unit in real time: the track motor driver adjusts the array element spacing to match the half-wavelength requirement under varying sound speeds to avoid beam grating lobe interference; the elevation motor driver adjusts the array pitch angle to adapt to the acoustic wave coverage angle at different water depths, and combines it with the time delay compensation of electronic beamforming to form space-time joint focusing. Its role is to break through the beam control limits of fixed arrays through physical array reconstruction, solve the problem of sound field distortion caused by salinization or suspended matter, and reduce the sidelobe energy loss of electronic scanning. Ultimately, it can achieve improved mainlobe energy concentration and optimized multi-target resolution capability of acoustic imaging under complex hydrological conditions. It can also automatically trigger fault protection through preset safety thresholds to ensure the reliability of mechanical adjustment and system continuity.

[0095] S3. Perform closed-loop control of the acoustic system based on the adjusted phased array sound source formation. The specific steps of the acoustic closed-loop control are as follows:

[0096] S3.1. Delay parameter generation. The specific process of delay parameter generation is as follows:

[0097] S3.1.1. Data Input: Set the spatial coordinates of the transducers in the transducer array. The origin of the coordinate system is the geometric center of the transducer array. The X-axis of the coordinate system is along the longitudinal direction of the hull, and the Y-axis of the coordinate system is along the transverse direction of the hull. The transducer coordinates are set to (xi, yi), where i = (1, 2, 3, ..., 16). Set the angle of the transducer orientation relative to the normal direction of the transducer array to θ. Set the distance between the transducer array and the phased array sound source target to R. Set the sound speed to c. Then obtain the actual transducer spacing after the transducer position adjustment.

[0098] S3.1.2. Calculate the relative path difference: For the i-th transducer, its path difference relative to the array center is: Δd i =x i *cosθ+y i *sinθ;

[0099] S3.1.3. Calculate the theoretical time delay parameter: Convert the path difference of the transducer relative to the array center into a time difference: τ i =Δd i / c;

[0100] The spatial coordinate setting of the transducer array is to establish a Cartesian coordinate system with the geometric center as the origin, and define the position of each transducer as (x i ,y i ), combined with the heading angle θ, target distance R and corrected sound speed c, the path difference and delay parameters are calculated through the geometric acoustic model: path difference Δd i =x i·cosθ+y i sinθ, time delay τ i =Δd i / c achieves spatial beam synthesis; its function is to map the physical array parameters to a mathematical model, quantify the impact of the actual spacing after mechanical adjustment on beamforming, and dynamically correct θ and R in combination with an environmental adaptive algorithm to ensure the coherent superposition of sound waves in the target area. Among the supplementary mechanisms, real-time coordinate system calibration technology can correct coordinate offsets caused by mechanical deformation, while iterative optimization of R values under sound velocity gradient fields further improves beam focusing accuracy in complex sound fields, ultimately achieving precise control from physical layout to acoustic performance.

[0101] S3.1.4, Delay Quantization and Alignment:

[0102] The delay quantification formula is: τ quantized =round(τ i / 1ns)*1ns;

[0103] The calculation steps for inter-channel synchronization alignment are:

[0104] First find the maximum delay τ max =max(τ1,τ2,...,τ N ), the maximum value of N is 16;

[0105] So the relative delay of each channel is: Δτ i =τ max -τ i ;

[0106] Delay quantization and alignment discretizes the theoretical delay τi to 1ns accuracy and calculates the relative delay Δτi = τmax - τi based on the maximum delay τmax, achieving time synchronization and alignment of multi-channel signals. The quantization process adapts to the hardware clock resolution to avoid beam phase errors caused by the accumulation of delay mantissas. Synchronous alignment unifies the delay difference of each channel relative to τmax to ensure the coherent superposition of sound waves at the target point and suppress the sidelobe rise caused by time mismatch.

[0107] S3.1.5. Generate a delay table: The table content includes channel numbers and delay parameter values;

[0108] The purpose of generating a delay table is to provide executable timing control parameters for the signal generator. The underlying system drives the digital delay line hardware through binary delay codes. Combined with temperature compensation algorithms and fault-tolerance mechanisms, this ultimately achieves nanosecond-level precision in beam temporal and spatial consistency control, providing underlying timing assurance for high-resolution acoustic imaging.

[0109] S3.2, dynamic verification, the specific steps of dynamic verification are:

[0110] S3.2.1. Preparation: First, set the parameters of the super-resolution imaging signal generator, then calibrate the power amplifier unit to the rated power. Then, connect the digital oscilloscope to the hydrophone probe and set the trigger mode to rising edge trigger. At the same time, collect the static water background noise and test the initial sound velocity c0.

[0111] During the preparation phase, the transmission parameters of the super-resolution imaging signal generator are set, the power amplifier unit is calibrated to the rated power, a digital oscilloscope is connected to the hydrophone probe and set to rising-edge trigger mode, and the background noise spectrum of the static water area and the initial sound velocity c0 are simultaneously collected. The principle is to establish a system baseline state: the signal parameters define the time-frequency characteristics of acoustic imaging, the power amplifier calibration ensures the stability of the transmission energy, the background noise analysis provides a reference spectrum for subsequent adaptive filtering, and the initial sound velocity c0 serves as the baseline value for the environmental compensation algorithm. In the supplementary phase, the cross-correlation method is used to verify the clock synchronization deviation between the hydrophone and the signal generator, and the power amplifier linearity is tested by white noise injection. Ultimately, a repeatable and standardized test environment is provided for dynamic verification, ensuring the accuracy of acoustic performance evaluation and the effectiveness of system robustness verification.

[0112] S3.2.2. Transmission triggering and data acquisition: The command terminal sends a single pulse signal to the super-resolution imaging signal generator. Each channel of the phased array acoustic source then transmits the signal in a time-sharing manner according to a preset delay table. The four-channel acquisition unit then synchronously collects the direct wave signal returned by the transponder, acquires the target reflected wave signal through the hydrophone module, and uses an oscilloscope to obtain the time-domain waveform of the sound pressure of the hydrophone module.

[0113] The transmission trigger and data acquisition system sends a single pulse trigger signal to the super-resolution imaging signal generator through the command terminal, driving each channel of the phased array sound source to transmit the coded signal in a time-sharing manner according to the preset delay table. At the same time, the four-channel acquisition unit synchronously captures the direct wave signal of the transponder, the hydrophone module receives the target reflected wave signal, and the digital oscilloscope records the sound pressure time domain waveform and performs cross-correlation analysis with the theoretical waveform. The principle is to achieve spatiotemporal alignment of the transmit-receive link through strict timing control. Its functions include: verifying delay synchronization, extracting target echo delay and Doppler frequency shift, and quantifying signal propagation distortion. A reference clock distribution network can be introduced to ensure sub-microsecond synchronization between the acquisition unit and the signal generator, and combined with pulse compression technology to enhance the extraction capability of weak reflected signals, providing high-confidence spatiotemporal joint feature data for subsequent imaging algorithms.

[0114] S3.2.3. Delay synchronization verification: Use an oscilloscope to measure the trigger time difference of each channel, and determine the delay error value between channels based on the water environment;

[0115] Delay synchronization verification uses a high-precision digital oscilloscope to measure the trigger time difference of each channel, compare the preset delay table with the actual transmission timing deviation, and dynamically set the maximum allowable error threshold between channels based on environmental characteristics such as the water sound velocity gradient and multipath effect. Its principle is to quantify the inconsistency of hardware link delay through time domain waveform cross-correlation analysis and eye diagram observation. Its functions include: ensuring the phase coherence of beamforming and suppressing imaging artifacts caused by delay mismatch. An adaptive error compensation mechanism can be introduced to automatically trigger the recalculation of the delay table and the power balancing of the power amplifier unit when an out-of-limit error is detected. At the same time, the PTP protocol is combined to reduce the impact of system reference clock drift, ultimately ensuring the robustness of beam spatiotemporal control and the repeatability and accuracy of the imaging system under complex sound field conditions.

[0116] S3.2.4. Beam focusing effect verification: First calculate the main lobe amplitude and the ratio of the first side lobe to the main lobe amplitude. The verification formula is: Side lobe suppression ratio = 20log 10 (A side / A main ), where Amain is the main lobe peak amplitude, and Aside is the maximum side lobe peak amplitude;

[0117] The beam focusing effect is verified by calculating the ratio of the main lobe peak amplitude to the maximum sidelobe peak amplitude, and quantifying the beam energy concentration using the sidelobe suppression ratio formula. The principle is to evaluate the effectiveness of delay control and formation adjustment through acoustic field radiation pattern analysis. Its functions include: verifying the sharpness of the beam main lobe under mechanical-electronic coordinated control and suppressing imaging false alarms caused by sidelobe interference; it can be combined with near-field acoustic holography technology to reconstruct the three-dimensional sound field distribution, identify abnormal sidelobes caused by array edge diffraction effects, and introduce a dynamic weighting algorithm to optimize the array element excitation weights. At the same time, the influence of external interference is eliminated by comparing the ambient noise background, ultimately ensuring that the system can still achieve high-fidelity beam focusing in complex sound fields, providing core acoustic performance guarantee for underwater target imaging;

[0118] S3.2.5, Signal Integrity Verification: Check that there is no distortion within the transmitted signal bandwidth and that harmonic distortion is ≤-40dBc, indicating that the spectrum is complete; perform autocorrelation analysis on the Costas coded signal, and if the main-to-sidelobe ratio is ≥13dB, the coding is verified;

[0119] Signal integrity verification ensures the fidelity of acoustic signals in the transmission-transmission-reception link by analyzing the frequency domain characteristics and time domain autocorrelation characteristics of the transmitted signal. Spectral verification uses FFT analysis to detect harmonic spurs caused by power amplifier nonlinearity, and time domain verification evaluates the coding's ability to resist multipath interference through the sharpness of the autocorrelation peak. Its purpose is to avoid imaging blur and false sidelobe interference caused by signal distortion, while ensuring pulse compression gain for weak target detection. Pre-distortion correction algorithms can be introduced to compensate for power amplifier nonlinearity, combined with dynamic bandwidth allocation to avoid frequency band congestion, and underwater channel equalizers can be used to suppress multipath delay interference. Ultimately, a full-link quality control system is established from signal generation to channel adaptation, laying the physical layer foundation for high-confidence acoustic imaging.

[0120] S3.2.6. Dynamic environmental adaptability verification: Trigger sound velocity correction by rapidly injecting salinity change data; and verify transmit power compensation under turbid water scenario changes by injecting high turbidity water into the experimental chamber.

[0121] The dynamic environmental adaptability verification triggers real-time correction of sound velocity by rapidly injecting salinity mutation data, and injects high turbidity water into the experimental chamber to simulate turbid waters, and compares and verifies the system's compensation ability for sound wave attenuation. The principle is to test the system's response speed to sudden changes in environmental parameters and the effectiveness of the adaptive strategy through extreme environmental simulation. Its functions include: verifying the stability of beam pointing under sudden changes in sound velocity gradient, and ensuring that the target echo signal-to-noise ratio in turbid waters is maintained at ≥20dB. A multi-physics field coupling model can be introduced to predict the optimal compensation parameters in complex environments, and a power-bandwidth joint control algorithm can be combined to reduce multipath interference. Dynamic balance is achieved through a closed-loop feedback mechanism, ultimately ensuring that the system can still maintain an imaging effective coverage rate of >85% and a positioning error rate of ≤5% under extreme hydrological conditions such as salinity jump layers and sediment suspension.

[0122] S4. Design a fault tolerance mechanism and formulate corresponding response measures according to the fault type:

[0123] 1) When the multi-parameter water quality sensor fails, historical data interpolation is enabled to avoid interruption of the environment adaptive algorithm. Specifically:

[0124] 1.1) Using the ARIMA time series prediction model, combined with real-time trends in water temperature and depth data, we dynamically compensate for missing salinity and turbidity data. For example, when a sensor fails, we use a Kalman filter to predict the current parameter value based on the sound velocity, salinity, and turbidity correlations over the past 30 minutes, with a prediction error within ±3%.

[0125] 1.2) The historical data window is set to 30 minutes. After the time window is exceeded, it automatically switches to conservative mode and cross-validates the interpolation validity by inverting the acoustic field characteristics of the hydrophone.

[0126] 1.3) Phase rotation compensation is introduced. When generating the delay table, a virtual array element position offset Δx' = Δx*(1+kc) is added, where kc is the track displacement obstruction proportional factor. Based on the actual movable state of the array element, the power weight of the power amplifier unit is dynamically adjusted to avoid local overheating and optimize energy efficiency.

[0127] 1.4) Determine the track jam status by combining the motor drive current mutation and position encoder feedback;

[0128] 2) When the track of the movable power amplifier track module is stuck, it switches to electronic beamforming mode, dynamically expanding the delay parameter range to compensate for the physical formation, sacrificing ≤3dB sidelobe suppression to maintain basic detection capabilities. Specifically:

[0129] 2.1) Real-time reading of the drive current, position encoder feedback, and temperature sensor data of the track motor driver and elevation motor driver. If the motor current continues to exceed the limit and the position encoder data does not change, a fault alarm is triggered;

[0130] 2.2) Expanding on the original delay quantization range, by adding virtual delay to compensate for the frozen physical displacement, assuming that the actual displacement of the i-th transducer is blocked due to track jamming, the corrected delay is:

[0131] τ i ′=τ i +k i *Δτ max ;

[0132] Where Δτ max To compensate for the maximum allowed delay, an additional phase offset is applied to the transducers of the frozen formation to compensate for the lack of physical displacement:

[0133] φ i =2πf*τ i ';

[0134] Wherein, f is the center frequency of the transmitted signal;

[0135] 2.3) Dynamically adjust the output power of the power amplifier unit according to the actual movable state of the array element:

[0136] P i =P max *(1-0.2k i );

[0137] Through the closed-loop feedback of the Class D amplifier of the power amplifier unit, the output impedance matching is monitored in real time to prevent hardware damage caused by power imbalance;

[0138] 2.4) The original beamforming algorithm used an adaptive sidelobe suppression algorithm, such as minimum variance distortionless response (MVDR). After switching, it is downgraded to a delayed sum algorithm, sacrificing some sidelobe suppression capability in exchange for reduced computational complexity and ensuring real-time performance.

[0139] 3) When the network is interrupted, data is cached locally for ten minutes and then transmitted after recovery. The local cache uses dual RAID1 solid-state disk storage and is embedded with a Beidou short message module to enable emergency backhaul of critical data.

[0140] The fault-tolerance mechanism ensures system continuity by pre-setting a multi-level redundancy strategy. Its principle is to build a multi-level fault-tolerant system through hardware redundancy, algorithm degradation and communication heterogeneous design. Its functions include: ensuring the minimum functional availability of the system under extreme faults and reducing the risk of data loss. Fault tree analysis can be introduced to realize a self-diagnosis-self-repair closed loop, combined with FPGA hard real-time control to quickly switch redundant links, ultimately achieving high-reliability shipboard operation requirements.

[0141] In this embodiment, water quality, inertial navigation and acoustic data are integrated in real time through an environmental adaptive algorithm to dynamically optimize the phased array sound source formation: the sound speed is corrected and the time delay parameters are generated based on the Leroy formula, and a high-precision servo motor is driven to adjust the transducer spacing and pitch angle. Combined with electronic beamforming, space-time joint focusing is achieved; a single pulse coded signal is used to trigger synchronous acquisition and dynamic verification, and the system robustness is ensured through extreme environment simulation; a three-level fault-tolerant mechanism is used to ensure continuous operation under fault conditions, and ultimately the main lobe is improved in complex waters. The energy concentration and imaging resolution are improved, and high-precision adaptive underwater target detection and imaging are achieved.

[0142] The above description is merely a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any person skilled in the art may utilize the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes for application in other fields. However, any simple modification, equivalent change, and modification of the above embodiments made in accordance with the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A shipborne underwater acoustic imaging information processing and display control system, characterized in that: include: A core control unit, comprising a command terminal and a phased array control host computer; An acoustic emission unit, comprising a frequency division imaging signal generator, a movable power amplifier track module, and a phased array sound source; A data acquisition unit, comprising a four-channel acquisition unit and a hydrophone module; An environmental perception auxiliary unit, comprising a multi-parameter water quality sensor and an acoustic detection acquisition unit; A positioning unit, comprising a GPS module and an inertial navigation module; The movable power amplifier track module includes a movable track, a track servo controller, a track motor driver, and an elevation motor driver. The movable track is used to install the transducer array on the hull. The track servo controller is connected to the track motor driver and the elevation motor driver by signal. The phased array sound source includes a power amplifier unit and a transducer array, wherein the transducer array includes sixteen transducers, and the transducers receive electrical signals from the power amplifier unit; The accusation terminal is connected to the super-resolution imaging signal generator via a 10 Gigabit network, and the super-resolution imaging signal generator is connected to two power amplifier units via sixteen channels, each of which is allocated eight channels, and each of which is connected to eight transducers, and each of which is connected to one channel. The command terminal is connected to the phased array control host computer via a 10 Gigabit network, and the phased array control host computer is connected to the hydrophone and the four-channel acquisition unit via two Gigabit networks respectively; The control terminal is connected to the track servo controller via a shielded twisted pair cable, and the track servo controller is connected to the track motor driver and the elevation motor driver via a CAN bus. The accusation terminal is connected to a digital oscilloscope via a USB 3.0 channel, and the probe of the digital oscilloscope is connected to the hydrophone; The accusation terminal is connected to the data storage server via an optical fiber, and the data storage server is connected to the acoustic detection acquisition unit and the multi-parameter water quality sensor data via a SAS interface; The accusation terminal is connected to the GPS module via RS232, and the accusation terminal is connected to the inertial navigation module via a 10 Gigabit network.

2. The underwater acoustic imaging shipborne information processing and display control system according to claim 1, characterized in that: The command terminal is equipped with an environment-adaptive algorithm for multi-source data fusion processing, global task scheduling, and human-computer interaction interface rendering. The phased array control host computer receives hydrophone data in real time, calculates the sound source channel delay parameters, and controls the signal generator and power amplifier unit. The super-resolution imaging signal generator generates frequency-adjustable / phase-modulated transmission signals and receives the delay parameters of the phased array control host computer and outputs them in different channels. The movable power amplifier track module adjusts the array element spacing of the phased array sound source according to changes in water quality and adjusts the array pitch angle of the phased array sound source to adapt to different water depths. The transducer array converts electrical signals into sound waves and can change the spatial layout of the transducer array when the movable power amplifier track module receives mechanical adjustment instructions. The four-channel acquisition unit is used to synchronously collect transponder signals and transmit time difference data to the core control unit in real time. The hydrophone module is used to receive reflected sound wave signals and provide raw acoustic data for imaging. The multi-parameter water quality sensor is used to provide real-time feedback of water environment data and trigger the update of adaptive algorithm parameters. The acoustic detection and acquisition unit is used to monitor the direct wave of the phased array sound source and provide beam pointing calibration data.

3. The underwater acoustic imaging shipborne information processing and display control system according to claim 1, characterized in that: The environment adaptive adjustment algorithm is used to optimize the formation of the phased array sound source according to the detected water quality data, and specifically includes the following steps: S1, first perform environmental perception and parameter calculation; S2, then mechanically and dynamically adjust the movable amplifier track module; S3. Performing closed-loop control of the acoustic system based on the adjusted phased array sound source formation; S4. Design a fault-tolerant mechanism.

4. The underwater acoustic imaging shipborne information processing and display control system according to claim 3, characterized in that: In step S1, the specific process of environment perception and parameter calculation is as follows: S1.

1. First, collect environmental data: use a multi-parameter water quality sensor to obtain the water area's sound velocity, salinity, turbidity, and water temperature. Then, use the inertial navigation module to obtain the AUV's attitude data. Finally, use the hydrophone module to collect the ambient noise background spectrum. S1.

2. Perform the sound velocity compensation calculation: The sound velocity compensation calculation obtains the correction coefficient. The specific steps are as follows: Using Leroy's correction formula: c=1449.2+4.6T-0.055T 2 +1.34(S-35)+0.016D+0.07(NTU); The calculation process is as follows: when temperature T = 15°C, salinity S = 34.5‰, depth D = 200m, and turbidity NTU = 8, c = 1481.6m / s; Comparing the default value c0 = 1500m / s, the correction factor is generated: k c =c / c0=0.9877; S1.

3. Finally, formulate the transducer array formation optimization decision: formulate the transducer array formation adjustment plan based on the environmental perception data, system hardware limitations and acoustic performance.

5. The underwater acoustic imaging shipborne information processing and display control system according to claim 3, characterized in that: In step S2, during the control process of the position of the phased array sound source on the movable power amplifier track module, the track servo controller receives the adjustment instruction and then controls the start and stop of the track motor driver and the elevation motor driver to adjust the position of the phased array sound source unit installed on the track.

6. The underwater acoustic imaging shipborne information processing and display control system according to claim 3, characterized in that: In step S3, the specific steps of acoustic closed-loop control are: S3.1, delay parameter generation; S3.

2. Dynamic verification.

7. The underwater acoustic imaging shipborne information processing and display control system according to claim 3, characterized in that: In step S4, in the fault tolerance mechanism design, corresponding response measures are formulated according to the fault type: 1) When the multi-parameter water quality sensor fails, historical data interpolation is enabled; 2) When the track of the movable amplifier track module is stuck, switch to the electronic beamforming mode; 3) When the network is interrupted, data is cached locally for ten minutes and then uploaded after the network is restored.

8. The underwater acoustic imaging shipborne information processing and display control system according to claim 6, characterized in that: In step 3.1, the specific process of generating the delay parameters is as follows: S3.1.

1. Data Input: Set the spatial coordinates of the transducers in the transducer array. The origin of the coordinate system is the geometric center of the transducer array. The X-axis of the coordinate system is along the longitudinal direction of the hull, and the Y-axis of the coordinate system is along the transverse direction of the hull. The transducer coordinates are set to (xi, yi), where i = (1, 2, 3, ..., 16). Set the angle of the transducer orientation relative to the normal direction of the transducer array to θ. Set the distance between the transducer array and the phased array sound source target to R. Set the sound speed to c. Then obtain the actual transducer spacing after the transducer position adjustment. S3.1.

2. Calculate the relative path difference: For the i-th transducer, its path difference relative to the array center is: Δd i =x i *cosθ+y i *sinθ; S3.1.

3. Calculate the theoretical time delay parameter: Convert the path difference of the transducer relative to the array center into a time difference: τ i =Δd i / c; S3.1.4, Delay Quantization and Alignment: The delay quantification formula is: τ quantized =round(τ i / 1ns)*1ns; The calculation steps for inter-channel synchronization alignment are: First find the maximum delay τ max =max(τ1,τ2,...,τ N ), the maximum value of N is 16; So the relative delay of each channel is: Δτ i =τ max -τ i ; S3.1.

5. Generate a delay table: The table content includes the channel number and delay parameter value.

9. The underwater acoustic imaging shipborne information processing and display control system according to claim 6, characterized in that: In step 3.2, the specific steps of dynamic verification are: S3.2.

1. Preparation: First, set the parameters of the super-resolution imaging signal generator, then calibrate the power amplifier unit to the rated power. Then, connect the digital oscilloscope to the hydrophone probe and set the trigger mode to rising edge trigger. At the same time, collect the static water background noise and test the initial sound velocity c0. S3.2.

2. Transmission triggering and data acquisition: The command terminal sends a single pulse signal to the super-resolution imaging signal generator. Each channel of the phased array acoustic source then transmits the signal in a time-sharing manner according to a preset delay table. The four-channel acquisition unit then synchronously collects the direct wave signal returned by the transponder, acquires the target reflected wave signal through the hydrophone module, and uses an oscilloscope to obtain the time-domain waveform of the sound pressure of the hydrophone module. S3.2.

3. Delay synchronization verification: Use an oscilloscope to measure the trigger time difference of each channel, and determine the delay error value between channels based on the water environment; S3.2.

4. Beam focusing effect verification: First calculate the main lobe amplitude and the ratio of the first side lobe to the main lobe amplitude. The verification formula is: Side lobe suppression ratio = 20log 10 (A side / A main ), where A main is the main lobe peak amplitude, A side is the maximum sidelobe peak amplitude; S3.2.5, Signal Integrity Verification: Check that there is no distortion within the transmitted signal bandwidth and that harmonic distortion is ≤-40dBc, indicating that the spectrum is complete; perform autocorrelation analysis on the Costas coded signal, and if the main-to-sidelobe ratio is ≥13dB, the coding is verified; S3.2.

6. Verification of dynamic environmental adaptability: Trigger the sound velocity correction by rapidly injecting salinity change data; and verify the transmission power compensation under turbid water scene changes by injecting high turbidity water into the experimental chamber.

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