Unmanned survey vessel control method, system and circuit board based on posture adaptive compensation

Abstract

The application provides an unmanned surveying ship control method, system and circuit board based on attitude adaptive compensation, relates to the technical field of unmanned surveying ship control, and the method comprises the following steps: receiving an attitude compensation measurement trigger signal; collecting original angular rate and linear acceleration data of a ship body in real time according to the attitude compensation measurement trigger signal; and obtaining real-time three-dimensional space attitude parameters of the ship body according to a preset rigid body kinematics differential equation, the original angular rate and the linear acceleration data. The application improves the depth operation precision of the unmanned ship in a complex hydrological environment.

Description

Technical Field

[0001] This invention relates to the field of unmanned survey vessel control technology, and in particular to unmanned survey vessel control methods, systems and circuit boards based on attitude adaptive compensation. Background Technology

[0002] In unmanned surface vessel (USV) hydrographic surveying and waterway exploration operations, the detection accuracy of ultrasonic detectors depends on the perpendicular orthogonality between the ultrasonic beam and the instantaneous water surface. Furthermore, the stability of the power supply chain and the real-time performance of attitude calculations jointly determine the operational reliability in complex aquatic environments. However, existing USVs exhibit the following technical shortcomings when operating under actual water surface conditions: First, the ship's hull is continuously subjected to roll and pitch motions due to wave disturbances, and the raw data from the inertial measurement unit is affected by high-frequency mechanical vibration noise and sensor installation misalignment errors. Traditional attitude calculation methods often use direct integration or simple filtering, which easily leads to numerical accumulation drift and makes it difficult to accurately obtain the ship's real-time three-dimensional spatial attitude parameters under dynamic water surface conditions.

[0003] Secondly, the lack of integral correction for the deviation between the actual angular displacement and the reverse compensation angular displacement, as well as kinematic compensation correction for the propagation path of the acoustic wave slant range, results in the water depth data containing geometric distortion of the acoustic path introduced by the ship's tilt, making it difficult to guarantee the accuracy of depth measurement. Summary of the Invention

[0004] This invention provides a control method, system, and circuit board for unmanned survey vessels based on attitude adaptive compensation, which improves the accuracy of depth sounding operations of unmanned vessels in complex hydrological environments.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: Firstly, a control method for an unmanned measurement vessel based on attitude adaptive compensation, the method comprising: Step 1: Receive the attitude compensation measurement trigger signal; based on the attitude compensation measurement trigger signal, collect the original angular rate and linear acceleration data of the hull in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, obtain the real-time three-dimensional spatial attitude parameters of the hull. Step 2: Based on the real-time three-dimensional spatial attitude parameters of the hull, construct the direction cosine transformation matrix from the hull carrier coordinate system to the horizontal reference system of the water surface; according to the direction cosine transformation matrix, calculate the reverse compensation angle required for the ultrasonic detector to maintain normal emission; according to the reverse compensation angle, combine the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to perform dynamic feedforward compensation, and obtain the servo drive pulse sequence. Step 3: Drive the ultrasonic detector to perform deflection action based on the servo motor driven pulse sequence, and collect the actual rotation angle displacement of the ultrasonic detector in real time; perform deviation integral correction based on the actual rotation angle displacement and the reverse compensation angle, and dynamically adjust the ultrasonic detector to keep the main lobe axis of the transmitted beam continuously orthogonal to the instantaneous water surface; receive the underwater sound wave reflection echo and remove the sound path geometric distortion caused by the hull tilt, and use the reverse compensation angle to perform kinematic compensation correction on the sound wave slant range propagation path to obtain vertical water depth data.

[0006] Secondly, the unmanned measurement vessel control system based on attitude adaptive compensation includes: The acquisition module is used to receive attitude compensation measurement trigger signals; based on the attitude compensation measurement trigger signals, it acquires the original angular rate and linear acceleration data of the hull in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, it obtains the real-time three-dimensional spatial attitude parameters of the hull. The module is used to construct the direction cosine transformation matrix from the ship's carrier coordinate system to the horizontal reference system of the water surface based on the real-time three-dimensional spatial attitude parameters of the ship; according to the direction cosine transformation matrix, the reverse compensation angle required for the ultrasonic detector to maintain normal emission is calculated; according to the reverse compensation angle, dynamic feedforward compensation is performed in combination with the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to obtain the servo drive pulse sequence. The correction module is used to drive the ultrasonic detector to perform deflection actions based on the servo drive pulse sequence and to collect the actual angular displacement of the ultrasonic detector in real time; to perform deviation integral correction based on the actual angular displacement and the reverse compensation angle, and to dynamically adjust the ultrasonic detector so that the main lobe axis of the transmitted beam is continuously orthogonal to the instantaneous water surface; to receive the underwater acoustic wave reflection echo and remove the acoustic path geometric distortion caused by the hull tilt, and to perform kinematic compensation correction on the slant range propagation path of the acoustic wave using the reverse compensation angle to obtain the vertical water depth data.

[0007] Thirdly, the unmanned measurement vessel control circuit board based on attitude adaptive compensation includes an MCU that receives a stable operating voltage provided by the first buck module for implementing the method, and further includes: The backup lithium battery is encapsulated inside a white casing. When the main battery pack of the unmanned vessel is not turned on, it outputs the battery voltage, which is then boosted by a boost circuit to power the receiver. The receiver receives the remote control signal from the remote controller and outputs a high-level signal, which turns on the main battery pack switch of the unmanned boat through the chip. After the main battery pack is turned on, the receiver switches to the main battery pack for power supply, and at the same time the charging circuit charges the backup lithium battery and indicates the charging and stop status. The delayed power-on module receives the voltage output by the main battery pack after it is powered on, sets the delay time through a physical adjustment knob, and controls the first step-down module to power on in stages with delayed power-on. The first step-down module starts after receiving the enable control of the delayed power-on module, converts the main battery pack voltage into the required operating voltage, and supplies power to the MCU, satellite positioning module and network module. The satellite positioning module starts after receiving power from the first step-down module. It is directly controlled by the network module and outputs positioning, orientation and timing data. The network module receives control commands from the MCU, parses the positioning, orientation, and timing data output by the satellite positioning module, parses the transducer attitude sensor data, and sends the parsing results back to the MCU. The parameter file storage module receives read and write commands from the MCU and connects to an external computer via a communication bus interface to modify parameters. The navigation control module receives navigation control commands processed by the MCU and positioning and orientation data parsed by the network module, and completes navigation control, radar data parsing, and two-way wireless data communication with the ground station. The communication bus interface has two independent interfaces, which are responsible for the transmission of signal communication links and high-current power supply circuits, respectively.

[0008] The above-described solution of the present invention has at least the following beneficial effects: Through multi-level command verification, smooth dual-power supply switching, and closed-loop charging and discharging management mechanisms, software-level fault tolerance and seamless migration of the power supply link are achieved. Based on effective filtering of interference pulses and prevention of accidental triggering, the risk of voltage drops during switching transients is eliminated through overlapping power supply windows and dynamic voltage threshold monitoring. Simultaneously, it adapts to periodic power status acquisition and closed-loop management strategies, improving the power-on reliability, power system safety, and long-term standby endurance of the unmanned surface vessel under complex operating conditions. A highly robust attitude calculation link is constructed by performing coordinate system projection transformation and high-frequency noise filtering on inertial measurement data using rigid body kinematic differential equations. This design effectively isolates high-frequency mechanical vibration noise and sensor installation misalignment errors, suppresses numerical integration cumulative drift in real time, and obtains real-time three-dimensional spatial attitude parameters of the hull, including roll angle, pitch angle, and rate of change of angular velocity.

[0009] By constructing a direction cosine transformation matrix from the ship's coordinate system to the horizontal reference system of the water surface, the reverse compensation angle required for the ultrasonic detector to maintain normal transmission is calculated. Combined with static friction torque, load rotational inertia, and fluid damping characteristics, dynamic feedforward compensation is performed to generate a servo drive pulse sequence with adaptive inertia adjustment. This scheme upgrades pure geometric angle compensation to comprehensive dynamic compensation, effectively overcoming low-speed crawling phenomena and nonlinear load disturbances. It ensures that the detector can track the reverse compensation angle in real time with high dynamic response accuracy. Through closed-loop deviation integral correction between the actual angle displacement and the reverse compensation angle, continuous orthogonal locking of the main lobe axis of the transmitted beam to the instantaneous water surface is achieved. The reverse compensation angle is used to perform kinematic compensation correction on the slant range propagation path of the sound wave, dynamically eliminating the geometric distortion of the sound path introduced by the ship's tilt. The slant range propagation path is strictly projected onto the vertical normal to obtain vertical water depth data, improving the depth measurement accuracy of the unmanned surface vessel in complex hydrological environments. Attached Figure Description

[0010] Figure 1 This is a flowchart illustrating the unmanned measurement vessel control method based on attitude adaptive compensation provided in an embodiment of the present invention.

[0011] Figure 2 This is a schematic diagram of an unmanned measurement vessel control system based on attitude adaptive compensation provided in an embodiment of the present invention.

[0012] Figure 3 This is a schematic diagram of the control circuit board structure of an unmanned measurement vessel based on attitude adaptive compensation, provided by an embodiment of the present invention. Detailed Implementation

[0013] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0014] like Figure 1 As shown, embodiments of the present invention propose a control method for an unmanned measurement vessel based on attitude adaptive compensation, the method comprising the following steps: Step 1: Receive the attitude compensation measurement trigger signal; based on the attitude compensation measurement trigger signal, collect the original angular rate and linear acceleration data of the hull in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, obtain the real-time three-dimensional spatial attitude parameters of the hull. Step 2: Based on the real-time three-dimensional spatial attitude parameters of the hull, construct the direction cosine transformation matrix from the hull carrier coordinate system to the horizontal reference system of the water surface; according to the direction cosine transformation matrix, calculate the reverse compensation angle required for the ultrasonic detector to maintain normal emission; according to the reverse compensation angle, combine the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to perform dynamic feedforward compensation, and obtain the servo drive pulse sequence. Step 3: Drive the ultrasonic detector to perform deflection action based on the servo motor driven pulse sequence, and collect the actual rotation angle displacement of the ultrasonic detector in real time; perform deviation integral correction based on the actual rotation angle displacement and the reverse compensation angle, and dynamically adjust the ultrasonic detector to keep the main lobe axis of the transmitted beam continuously orthogonal to the instantaneous water surface; receive the underwater sound wave reflection echo and remove the sound path geometric distortion caused by the hull tilt, and use the reverse compensation angle to perform kinematic compensation correction on the sound wave slant range propagation path to obtain vertical water depth data.

[0015] In this embodiment of the invention, by employing attitude adaptive compensation technology, the original angular rate and linear acceleration data of the hull are collected in real time, and the real-time three-dimensional spatial attitude parameters are calculated by combining the rigid body kinematic differential equations. A direction cosine transformation matrix from the hull carrier coordinate system to the water surface horizontal reference system is constructed to calculate the reverse compensation angle. At the same time, feedforward compensation is completed by combining dynamic characteristics, and the ultrasonic detector is dynamically adjusted by deviation integral correction. Furthermore, the underwater acoustic wave reflection echo is subjected to sound path geometric distortion removal and kinematic compensation correction. This overcomes the technical problems of hull attitude deviation caused by wave disturbance during unmanned measurement vessel navigation, ultrasonic detector beam not being perpendicular to the instantaneous water surface, large water depth measurement error caused by geometric distortion of the sound wave slant range propagation path, and difficulty in precise driving of servo control due to mechanical and fluid disturbances. In this way, the main lobe axis of the ultrasonic detector beam is continuously orthogonal to the instantaneous water surface, effectively removing the measurement distortion caused by hull tilt, and improving the measurement accuracy, stability and adaptability of the unmanned measurement vessel's water depth data to complex water surface conditions.

[0016] In a preferred embodiment of the present invention, the process of generating the attitude compensation measurement trigger signal includes: The remote control command verification signal is acquired, and the remote control command verification signal is subjected to command encoding verification and key duration dual threshold judgment. After the verification is passed, the main battery pack is turned on and the dual power supply is smoothly switched to obtain a power-on ready status indicator. Specifically, the remote control command verification signal is acquired through the 433 receiver module in function area 1. The core MCU performs a 32-bit unique command identification code verification and a 16-bit CRC cyclic redundancy check on the remote control command verification signal. Commands that fail the verification are directly discarded. The high-level duration of the verified command is counted in real time using a high-precision timer. When the high-level duration falls, the command is ready to receive the command. When the preset short-press power-on effective duration range is entered, the unmanned vessel battery group switch is turned on through the chip. After the main battery group is turned on, the output voltage of the main battery group is collected at a 10ms cycle. When the output voltage of the main battery group is stable at 12V±10% of the rated operating range and remains stable for 500ms without fluctuation, the dual power supply smooth switching is triggered. The core MCU controls the overlapping power supply duration of the dual power supplies to be 200ms, switching the power supply of the 433 receiver from the backup lithium battery to the main battery group. After the switching is completed, the charging circuit is controlled to charge the backup lithium battery, the charging status indicator is lit, and a power-on ready status identifier is generated and latched.

[0017] Using the power-on ready status flag as the enabling condition, the system enters a low-power monitoring mode. After completing the communication bus initialization and power supply configuration of each sensor, a device collaborative operation benchmark is obtained. Specifically, the core MCU enters the low-power monitoring mode using the power-on ready status flag as the enabling condition, shuts down the clock and power supply branches of unnecessary peripherals, obtains the preset power-on delay time parameter through the physical adjustment knob of function area 3, and sends enable signals to each step-down module on the right in sequence according to the preset time interval. After receiving the enable signal, each step-down module outputs DC power of the corresponding voltage level to power the satellite positioning module, network module, navigation control module, attitude measurement unit, ultrasonic detector, and cabin environment monitoring equipment. The system completes the baud rate, data bits, stop bits, and parity bits configuration of the communication bus interface of the unmanned vessel's external modules, establishes communication links between modules, sends identification commands to each module in sequence, receives device status information returned by each module, confirms that all modules respond normally, and generates a device collaborative operation benchmark based on the response time and status information of each module. This benchmark includes the working clock frequency, data sampling period, and communication timing parameters of each module.

[0018] Using the equipment collaborative operation benchmark as the working cycle, the terminal voltage and charging current of the backup lithium battery are periodically collected. The collected data is matched with a preset charging control mode to generate a power closed-loop management command. Specifically, this includes: using the data sampling period in the equipment collaborative operation benchmark as the working cycle, collecting the terminal voltage and charging current of the backup lithium battery through the built-in analog-to-digital conversion channel, matching the collected terminal voltage and charging current data with a preset three-level charging control mode, and when the conditions are met... At this time, the pre-charge mode is executed, controlling the charging circuit to output a constant current. Charge the backup lithium battery when it meets the requirements. When in constant current charging mode, the charging circuit outputs a constant current. Charge the backup lithium battery when it meets the requirements. When in operation, the constant voltage charging mode is executed, controlling the charging circuit to output a constant voltage. Charge the backup lithium battery until the charging current reaches its maximum. Down to After charging is complete, the core MCU turns off the charging status indicator and turns on the charging complete indicator. During charging, the core MCU collects the body temperature of the backup lithium battery through the onboard temperature sensor. When satisfied When an abnormal temperature alarm signal is triggered, the core MCU immediately suspends charging and immediately disconnects the charging circuit when an overcharge, overcurrent, or short circuit fault is detected. The fault state is then latched. Based on the charging mode matching result and the fault detection result, a power closed-loop management instruction is obtained. This instruction includes the current charging stage, charging parameters, and fault state information. This is the real-time terminal voltage of the backup lithium battery. The pre-charge voltage threshold. This is the pre-charging current. The constant current charging cutoff voltage, For constant current charging current, The real-time charging current for the backup lithium battery. To stop the current during charging, This refers to the real-time body temperature of the backup lithium battery. The high temperature protection threshold, This is the low-temperature protection threshold.

[0019] Based on the power closed-loop management command, it is confirmed that both the backup lithium battery charging state and the main battery pack power supply state have entered the steady-state operating range. After the dual-path steady-state conditions of the power supply are met, a full-system measurement ready trigger command is sent to the attitude measurement and ultrasonic detection related sensors to generate an attitude compensation measurement trigger signal. Specifically, according to the power closed-loop management command, it is determined whether the backup lithium battery charging state has entered the steady-state operating range. When the backup lithium battery is in the constant voltage charging stage and the charging current is stable and fluctuates around Is, or when charging is completed, it is determined that the backup lithium battery charging state has entered the steady state. The output voltage Vm of the main battery pack is collected at a period of 10ms. When Vm is stable in the rated operating range of 12V±10% and remains stable for 500ms without fluctuation, it is determined that the main battery pack power supply state has entered the steady state. After the core MCU confirms that the steady-state conditions of both power supply channels are met, it sends a full-system measurement ready trigger command to the attitude measurement unit, ultrasonic detector, satellite positioning module, network module, navigation control module, onboard thermometer, and water ingress detection circuit board. Upon receiving the trigger command, the core MCU completes the internal register configuration and sensor calibration, enters the measurement waiting state, and receives the measurement ready confirmation signals returned by each module to obtain the attitude compensation measurement trigger signal.

[0020] In this embodiment of the invention, by employing a multi-level verification mechanism based on 433 wireless remote control commands and a dual-threshold judgment logic for button duration, combined with main battery pack conduction and dual-power seamless switching technology, it simultaneously achieves phased delayed power-on control, independent configuration of the communication bus, three-level segmented charging closed-loop management, all-dimensional charging protection, and a dual-path power steady-state judgment mechanism. Therefore, it overcomes the technical problems of existing unmanned vessel remote control power-on being easily triggered by interference, the risk of power interruption during dual-power switching, the power surge and communication conflict caused by the simultaneous start-up of modules when the system is powered on, the lack of refined control during the charging process leading to shortened battery life, and the abnormal data caused by starting measurement when the power supply is unstable. Thus, it achieves safe and reliable power-on process for unmanned vessels and stable system operation, and extends the service life of backup lithium batteries.

[0021] In a preferred embodiment of the present invention, step 1 above may include: Step 11: Receive the attitude compensation measurement trigger signal; based on the attitude compensation measurement trigger signal, acquire the raw angular rate of the three-axis gyroscope and the raw linear acceleration of the three-axis accelerometer of the inertial measurement unit; perform zero-bias calibration and temperature drift compensation on the raw angular rate and raw linear acceleration to obtain calibrated inertial measurement data. Specifically, this includes: after receiving the attitude compensation measurement trigger signal, waking up the inertial measurement unit to enter full-speed acquisition mode. The inertial measurement unit is integrated into the core area of ​​the unmanned vessel's main control circuit board. Power-on is completed by matching the delayed power-on sequence in functional area 3 of the circuit board, and a stable voltage is continuously supplied through the step-down module to ensure stable sensor operation. The external module communication bus interface independently handles data transmission, avoiding signal interference from the high-current power supply circuit on attitude data. The inertial measurement unit's built-in three-axis gyroscope synchronously acquires raw angular velocity data within the ship's three-dimensional space, while the three-axis accelerometer synchronously acquires raw linear acceleration data along the corresponding axis of the ship. All raw acquired data is uploaded to the core MCU in real time according to the preset sampling period of the equipment's collaborative operation benchmark. The chip retrieves the sensor factory calibration parameters embedded within the chip and performs channel-by-channel zero-bias calibration on the real-time received raw angular velocity and raw linear acceleration data to offset fixed acquisition errors caused by sensor static installation deviations and inherent component manufacturing errors. Throughout the data acquisition process, an onboard thermometer continuously monitors the cabin's operating temperature. Combined with the cabin's steady-state temperature data after cooling by the cooling fan, a preset temperature drift compensation model is matched to dynamically correct the signal offset of the sensor output under different temperature conditions. This offsets the temperature disturbances caused by the operation of heat-generating equipment such as the lithium battery protection board, depth sounder main unit, and power module within the cabin. After completing all error corrections, the calibrated inertial measurement data is output.

[0022] The preset temperature drift compensation model adopts a second-order polynomial fitting form, establishing independent temperature drift correction equations for the gyroscope and accelerometer respectively. The model parameters are obtained through full-temperature-range calibration before the equipment leaves the factory and are stored in the parameter file memory card. The temperature drift compensation calculation formula is as follows: ; ; In the formula: The triaxial angular rate data are after temperature drift compensation. The raw three-axis angular rate data collected by the gyroscope. This is the first-order temperature drift coefficient of the gyroscope's zero bias. This is the second-order temperature drift coefficient of the gyroscope with zero bias. The real-time cabin temperature is collected by an onboard thermometer. Calibrate the reference temperature for the sensor; The triaxial acceleration data are after temperature drift compensation. The raw triaxial acceleration data collected by the accelerometer The first-order temperature drift coefficient of the accelerometer zero bias. To determine the second-order temperature drift coefficient for the accelerometer's zero bias, the model calibration process was completed within a high and low temperature test chamber. The chamber temperature covered the actual operating temperature range of the unmanned surface vessel. Sufficient time was maintained at each temperature point to allow the sensor to reach thermal equilibrium. Static output data from the sensor was collected, and the sensor output data at different temperatures was fitted to obtain the temperature drift coefficient for each channel. During operation, the core MCU synchronously acquired temperature data from the onboard thermometer in each sampling cycle. This data was then substituted into the temperature drift compensation equation to calculate the corrected inertial measurement data, eliminating the influence of temperature changes on the sensor output. The zero bias calibration calculation satisfies the following formula: ; ; In the formula: To calibrate the triaxial angular rate data, The raw three-axis angular rate data collected by the gyroscope. Set a fixed zero bias error value for the gyroscope; To calibrate the triaxial acceleration data, The raw triaxial acceleration data collected by the accelerometer To fix the zero bias error value for the accelerometer.

[0023] Step 12: Perform multi-band adaptive filtering on the calibrated inertial measurement data to suppress high-frequency vibration noise and smooth the convergence of low-frequency attitude trends, obtaining filtered angular rate data and filtered linear acceleration data; extract the quasi-static gravitational acceleration projection component based on the filtered linear acceleration data. The filtered kinematic feature data is composed of the filtered angular rate data and the quasi-static gravitational acceleration projection component. Specifically, based on the calibrated inertial measurement data, which includes three-axis angular rate data and three-axis linear acceleration data, a multi-band adaptive filtering architecture is used to perform frequency segmentation processing on the two types of data respectively, achieving high-frequency vibration noise suppression and low-frequency attitude trend smoothing, while separating the dynamic acceleration component and the quasi-static gravitational acceleration projection component in the linear acceleration data. The component, multi-band adaptive filtering processing of three-axis angular rate data, adopts a two-stage cascaded FIR low-pass filter structure. The first stage is a high-frequency noise suppression filter, and the second stage is an adaptive trend smoothing filter. The coefficients of the two filters are pre-designed using the window function method and stored in the parameter file memory card. The first-stage high-frequency noise suppression filter is a 16th-order FIR low-pass structure with an upper cutoff frequency set to 20Hz and a stopband attenuation of 40dB. It is used to filter out high-frequency angular rate noise caused by hull mechanical vibration and water flow impact. There is no effective attitude information in this frequency band. The second-stage adaptive trend smoothing filter is an 8th-order FIR low-pass structure with an upper cutoff frequency set to 2Hz. It is used to smooth the low-frequency trend signal of hull attitude change and retain the effective attitude change component.

[0024] The adaptive adjustment mechanism is based on the rate of change of angular velocity data. It calculates the rate of change of angular velocity data in real time. When the rate of change exceeds a preset threshold, it is determined to be a condition of drastic attitude change, and the order of the second-stage filter is switched to 4th order to reduce signal phase delay and improve the response speed of attitude changes. When the rate of change is below the preset threshold, it is determined to be a stable condition, and the order of the second-stage filter is restored to 8th order to enhance noise suppression. The rate of change threshold is pre-stored in the parameter file storage card and can be adjusted according to the unmanned surface vessel's operating speed. The three-axis acceleration data is processed by component separation. The linear acceleration data processing adopts a two-stage filtering structure. The first stage is a high-frequency noise suppression filter, using a 16th-order FIR low-pass structure with an upper cutoff frequency set to 20Hz, filtering out high-frequency acceleration noise caused by hull mechanical vibration. The second stage is an adaptive low-pass trend filter, using a first-order recursive form with a lower cutoff frequency set to 0.1Hz, used to extract the quasi-static gravity acceleration projection component. Its calculation satisfies the following formula: ; ; ; In the formula, , , The current sampling period x axis, y axis, z The quasi-static gravitational acceleration projection component of the axis; , , Each represents the previous sampling period. x axis, y axis, z The quasi-static gravitational acceleration projection component of the axis; These are the adaptive low-pass filter coefficients; , , These are the current sampling periods. x axis, y axis, z Axial acceleration data, filtering coefficients The value range is 0.9~0.99. It calculates the fluctuation level of linear acceleration data in real time. When the fluctuation level exceeds a preset threshold, it increases. The value is adjusted to enhance the low-pass filtering effect and suppress interference from dynamic acceleration components; when the fluctuation level is below a preset threshold, the value is reduced. The value is used to accelerate the response speed of the gravity component. The threshold of the fluctuation level is pre-stored in the parameter file storage card and can be adjusted according to the water flow environment of the operating water area. The linear acceleration data is subtracted from the quasi-static gravity acceleration projection component to obtain the dynamic acceleration component. This component reflects the acceleration change caused by water flow impact and wave disturbance during the ship's motion. After the above processing, the three-axis angular rate data after suppressing high-frequency noise, the smoothed low-frequency attitude trend data, and the separated dynamic acceleration component and quasi-static gravity acceleration projection component are obtained.

[0025] Step 13: Perform a three-axis orthogonal rotation mapping on the filtered kinematic feature data to obtain the coordinate mapping relationship from the sensor coordinate system to the hull structure reference coordinate system; based on the coordinate mapping relationship, transform the sensor installation coordinate system to the hull structure reference coordinate system to obtain the hull reference system measurement data; based on the hull reference system measurement data, correct the sensor mechanical offset error to align the measurement main axis with the hull pitch axis, roll axis, and vertical axis to obtain the hull alignment angular rate data. Specifically, this includes: retrieving the preset spatial coordinate transformation calibration parameters in the parameter file storage card. These parameters are calibrated and stored before the equipment leaves the factory, supporting long-term access and subsequent fine-tuning updates; performing a three-axis orthogonal rotation mapping operation on the filtered kinematic feature data based on the calibration parameters; and establishing a unique corresponding coordinate mapping relationship between the sensor installation coordinate system and the hull structure reference coordinate system according to the spatial rigid body motion rules, eliminating the spatial position deviation between the two coordinate systems.

[0026] The spatial rigid body motion rule is the fundamental physical rule for three-dimensional spatial attitude calculation. This rule defines the hull of an unmanned surface vessel as an equivalent spatial rigid body structure. During spatial motion, the relative positions of all its particles remain fixed, without deformation or relative displacement. Any spatial attitude deviation of the spatial rigid body can be completely decomposed into independent rotational motions around three sets of mutually orthogonal coordinate axes, corresponding to roll rotation, pitch rotation, and bow rotation, respectively. The three sets of rotational motions are decoupled from each other, and a single rotational action will not change the spatial coordinate relationships of the other axes. Under the premise of a fixed rotational operation order, any real-time spatial attitude of the rigid body can be uniquely calculated through the cascade operation of the corresponding rotation matrices, without the problem of multiple solutions or incorrect solutions. For the water depth measurement operation scenario of an unmanned surface survey vessel, the bow rotation of the hull around the vertical axis will not change the vertical detection reference of the ultrasonic detector and will not affect the water depth measurement data. A fixed rotational order of first rolling and then pitch is adopted to construct two basic rotation matrices and perform cascade operations to obtain a complete coordinate transformation matrix. The calculation of the roll rotation matrix and the pitch rotation matrix satisfies the following formula: ; ; In the formula, The roll rotation matrix is ​​the matrix about the longitudinal axis of the ship. This refers to the ship's roll angle; This is the pitch and rotation matrix about the transverse axis of the ship. For the ship's pitch angle, the core MCU, based on the established coordinate mapping relationship, completely transforms and maps the filtered kinematic feature data from all sensor coordinate systems to the ship's structural reference coordinate system, obtaining measurement data in the ship's reference system with the ship's main structure as the reference. The core MCU matches the sensor's factory calibration parameters and the ship's mechanical structure installation reference parameters, performing axis-by-axis correction on the ship's reference system measurement data to compensate for mechanical misalignment errors and installation angle offset errors generated during sensor assembly. After correction processing, the principal axis of attitude measurement is made to strictly match the spatial position of the ship's inherent pitch, roll, and vertical axes, and finally outputs the ship's alignment angular rate data.

[0027] Step 14: For the hull alignment angular rate data, perform discrete-time Euler integration based on the preset rigid body kinematics differential equations to obtain the initial attitude angle estimate; based on the quasi-static gravitational acceleration projection components, correct the integral cumulative drift error of the initial attitude angle estimate in real time to obtain the initial roll angle and initial pitch angle. Specifically, this includes: based on the hull alignment angular rate data, which has undergone transformation and calibration between the sensor coordinate system and the hull carrier coordinate system, and whose axial reference is consistent with the hull structure axis, numerically solve the hull alignment angular rate data using discrete-time Euler integration based on the preset rigid body kinematics differential equations to derive the change in hull attitude angle and obtain the initial attitude angle estimate. The discrete-time Euler integration operation satisfies the following formula: ; ; In the formula, This is the initial roll angle estimate for the current sampling period. The roll angle value retained from the previous sampling period. This refers to the angular rate component about the longitudinal axis of the hull in the hull alignment angular rate data. Set a fixed sampling time interval for the system; This is the initial pitch angle estimate for the current sampling period. The pitch angle value retained from the previous sampling period. The angular rate component around the hull's transverse axis in the hull alignment angular rate data is based on the quasi-static gravity acceleration projection component, which is a low-frequency stable component obtained by low-pass filtering of the linear acceleration data. This component reflects the actual projection value of the gravity vector in the hull carrier coordinate system. Based on the initial attitude angle estimation value, the theoretical projection value of the gravity vector in the hull carrier coordinate system is calculated. The calculation of the theoretical projection value is based on the rigid body space transformation relationship and is derived from the initial attitude angle estimation value.

[0028] The error between the actual projected value and the theoretical projected value is calculated. This error reflects the cumulative drift error generated during the Euler integral. A proportional correction mechanism is used to multiply the error by a preset correction gain coefficient to obtain the correction compensation. This compensation is then used to correct the initial attitude angle estimate in real time, suppressing integral drift. The correction calculation satisfies the following formula: ; ; In the formula, This is the corrected initial roll angle. To preset the correction gain coefficient, This represents the error in the projection of gravity in the roll direction. The corrected initial pitch angle. The preset correction gain coefficient is the gravity projection error in the pitch direction. The value ranges from 0.01 to 0.1 and can be adjusted according to the dynamic characteristics of the operating environment. When the ship is in a stable sailing state, increase... This value accelerates the correction of drift errors; when the hull is in a state of violent motion, it reduces... The values ​​are reduced to minimize the interference of dynamic acceleration on the correction process. The corrected attitude angle data is subjected to amplitude limiting processing to restrict the range of roll and pitch angles. After the correction processing, the cumulative drift error generated by the integral operation is canceled out. The corrected angle data is matched with the actual spatial tilt state of the hull to obtain the initial roll and initial pitch angles.

[0029] Step 15: Differentiate the angular rate change sequence corresponding to the initial roll and pitch angles to obtain the instantaneous angular acceleration; based on the instantaneous angular acceleration, perform dynamic response compensation by combining the fluid dynamic damping characteristics and moment of inertia distribution to obtain the compensated angle and compensated angular rate; fuse the compensated angle, compensated angular rate, and instantaneous angular acceleration to obtain the real-time three-dimensional spatial attitude parameters of the hull, specifically including: extracting the angular rate change sequence corresponding to the initial roll and pitch angles within a continuous sampling period, solving for the instantaneous angular acceleration of the dynamic change in hull attitude through differential calculation, characterizing the real-time drastic change in hull attitude, the differential calculation formula is: In the formula, It is the instantaneous angular acceleration. The change in angular rate between adjacent sampling periods. Set a fixed sampling time interval for the system.

[0030] Based on preset hydrodynamic damping characteristic parameters and hull attitude rotational inertia distribution parameters of the unmanned surface vessel (USV), these two types of parameters are calibrated and fixed according to the hull structure dimensions, water entry volume, and navigation conditions. The core MCU, combined with instantaneous angular acceleration data, compensates for the fluid damping resistance caused by water flow impact and the rotational inertia effect caused by the hull structure's self-weight, improving the lag problem in the dynamic response of the hull attitude. It completes the dynamic response compensation of attitude data, outputs the compensated angle and angular rate, and performs full-domain fusion of the three dimensions of data: compensated angle, compensated angular rate, and instantaneous angular acceleration. It integrates the static angle information, dynamic rate information, and instantaneous change trend information of the hull attitude, and comprehensively calculates the real-time three-dimensional spatial attitude parameters of the hull. After the attitude parameters are generated, they are stored in real time to the parameter file storage card to complete local data retention. The data is parsed and packaged through the network module and transmitted to the ground station in real time, realizing remote synchronous monitoring of the USV's hull attitude data.

[0031] In this embodiment of the invention, by adopting a hierarchical attitude data processing logic, multiple technologies such as sensor zero-bias calibration, temperature drift compensation, multi-band adaptive filtering, coordinate system orthogonal correction, integral drift correction, and fluid dynamics dynamic compensation are integrated. Based on the modular hardware architecture of the unmanned vessel's main control circuit board, temperature control and heat dissipation system, stable power supply and communication mechanism, the entire chain of fine processing of attitude raw data from acquisition, correction, filtering, conversion to fusion output is completed. Therefore, it overcomes the attitude data anomalies caused by sensor installation deviation, ambient temperature changes, water flow vibration interference, integral calculation errors, and fluid damping disturbances during unmanned measurement vessels' surface operations, and outputs three-dimensional spatial attitude parameters that fit the actual motion state of the hull.

[0032] In a preferred embodiment of the present invention, step 2 above may include: Step 21: Based on the real-time three-dimensional spatial attitude parameters of the hull, extract the roll and pitch angles for the current sampling period; establish a hull carrier coordinate system with the rotation axis of the ultrasonic detector as the spatial origin, and establish a horizontal water surface reference system with a plane parallel to the still water surface as the reference. The hull carrier coordinate system and the horizontal water surface reference system together constitute a spatial coordinate system mapping relationship. Specifically, this includes: extracting the roll and pitch angles corresponding to the current sampling period from the real-time three-dimensional spatial attitude parameters of the hull. The real-time three-dimensional spatial attitude parameters of the hull are stored in a dedicated double-buffered buffer area inside the core MCU. Each sampling... The system performs a data update and cache switch periodically to avoid data read / write conflicts. A ship carrier coordinate system is established with the rotation axis of the ultrasonic detector as the spatial origin. The rotation axis of the ultrasonic detector coincides with the geometric center of the ship structure. This position is precisely calibrated by a three-dimensional coordinate measuring machine before the equipment leaves the factory. The X-axis of the ship carrier coordinate system points towards the bow along the longitudinal axis of the ship, the Y-axis points towards the starboard side along the transverse axis of the ship, and the Z-axis points vertically upward towards the top of the ship along the vertical axis of the ship. The three coordinate axes are orthogonal to each other, forming a right-handed coordinate system. The axes of the coordinate system are completely aligned with the reference of the ship's mechanical structure.

[0033] A horizontal reference system is established using a plane parallel to the still water surface as a reference. The origin of the horizontal reference system coincides with the origin of the ship's coordinate system. The X-axis points to geographic due north, the Y-axis points to geographic due east, and the Z-axis is perpendicular to the still water surface and points upwards towards the sky. The geographic orientation reference of the horizontal reference system is determined by RTK fixed solution data and timing data provided by the satellite positioning module. The satellite positioning module is directly controlled by the network module and outputs positioning, orientation, and timing functions. Its data is transmitted to the core MCU through the communication bus interface of the unmanned vessel's external module. The ship's coordinate system and the horizontal reference system together constitute a spatial coordinate system mapping relationship. The basic parameters of this mapping relationship are calibrated by a dedicated calibration device before the equipment leaves the factory. The calibration process is carried out on a horizontal calibration platform to ensure the accuracy of the coordinate system reference. The calibration data is stored in a parameter file storage card, which is installed near functional area 4 of the main control circuit board. It supports parameter reading and fine-tuning updates via a computer connected through the power supply interface, adapting to the needs of different ship structures, different installation positions, and different operating environments.

[0034] Step 22: Based on the spatial coordinate system mapping relationship and the roll angle, perform a rotational mapping around the longitudinal axis of the hull to obtain a transverse rotational transformation sub-matrix; based on the spatial coordinate system mapping relationship and the pitch angle, perform a rotational mapping around the transverse axis of the hull to obtain a longitudinal rotational transformation sub-matrix; perform a cascaded multiplication operation on the transverse and longitudinal rotational transformation sub-matrixes according to the rotation order of the hull's spatial attitude to obtain an initial spatial mapping matrix. Specifically, this includes: performing a rotational mapping operation around the longitudinal axis of the hull based on the spatial coordinate system mapping relationship and the extracted roll angle to obtain a transverse rotational transformation sub-matrix. The transverse rotational transformation sub-matrix describes the relationship between any spatial vector in the hull's carrier coordinate system and the water surface horizontal reference system when the hull rotates around the longitudinal axis. Linear transformation relationship: Based on the spatial coordinate system mapping relationship and the extracted pitch angle, a rotational mapping operation is performed around the hull's transverse axis to obtain the longitudinal rotation transformation sub-matrix. This sub-matrix describes the linear transformation relationship between two coordinate systems for any spatial vector when the hull rotates around its transverse axis. The transverse and longitudinal rotation transformation sub-matrices are then subjected to cascaded multiplication operations in a fixed rotation order (roll first, then pitch) to obtain the initial spatial mapping matrix. This fixed rotation order ensures the uniqueness of the attitude description. The selection of the rotation order is based on the motion characteristics of the unmanned surface vessel; the frequency of roll motion is higher than that of pitch motion. Processing high-frequency motion components can improve the stability of the attitude calculation. The calculation of the transverse and longitudinal rotation transformation sub-matrices satisfies the following formula: ; ; ; In the formula, This is the transverse rotation transformation submatrix about the longitudinal axis of the ship's hull. This represents the ship's roll angle during the current sampling period. This is the longitudinal rotation transformation submatrix about the transverse axis of the ship's hull. The pitch angle of the hull during the current sampling period; The initial spatial mapping matrix is ​​used for matrix operation. The matrix operation is performed by the core MCU hardware floating-point operation unit in functional area 4 of the main control circuit board. The operation result is stored in the high-speed cache inside the core MCU. During the operation, the core MCU monitors its own operating temperature in real time, and the onboard thermometer continuously collects the air temperature inside the chamber. When the temperature exceeds the preset threshold, the cooling fan starts automatically.

[0035] Step 23 involves performing orthogonal normalization iteration and determinant sign verification on the initial spatial mapping matrix to eliminate non-orthogonal distortion components caused by the accumulation of sensor numerical calculations, thereby obtaining a reference direction cosine transformation matrix that satisfies strict orthogonality constraints. Specifically, this includes performing orthogonal normalization iteration on the initial spatial mapping matrix. During the iteration process, the inner product of the first and second column vectors of the matrix is ​​calculated. This inner product value reflects the degree of non-orthogonality between the two vectors. The non-orthogonality error is evenly distributed to the first and second column vectors, and the two vectors are corrected respectively, so that the inner product of the corrected vectors approaches zero. The core MCU normalizes the corrected first and second column vectors so that the magnitude of both vectors is 1. The core MCU calculates the third column vector through the cross product operation of the first and second column vectors, ensuring that the third column vector is orthogonal to the first two column vectors and has a magnitude of 1.

[0036] The core MCU repeats the above iterative process until the absolute value of the inner product between all column vectors of the matrix is ​​less than a preset threshold. The preset threshold is set to 1e-6, which ensures calculation accuracy while controlling the number of iterations within a reasonable range. The determinant sign is checked on the orthogonally normalized matrix. The determinant value of the matrix is ​​calculated. When the determinant value is 1, the matrix maintains the right-hand rule, and the direction of the spatial vector will not change during coordinate system transformation. When the determinant value is -1, the matrix exhibits mirror distortion. The third column vector is inverted to correct the distortion and restore the determinant value to 1. Through the above processing, the non-orthogonal distortion components caused by the accumulation of sensor numerical calculations are eliminated, resulting in a reference direction cosine transformation matrix that satisfies strict orthogonal constraints. Each column of this matrix corresponds to the unit vector of a coordinate axis in the horizontal reference system of the water surface in the ship's carrier coordinate system, and each row corresponds to the unit vector of a coordinate axis in the ship's carrier coordinate system in the horizontal reference system of the water surface. After the reference direction cosine transformation matrix is ​​generated, it is compared with the matrix of the previous sampling period to verify whether the changing trend of the matrix elements conforms to the ship's motion law and to eliminate abnormal and sudden data.

[0037] Step 24: Based on the reference direction cosine transformation matrix, and combined with the rate of change of angular velocity in the real-time three-dimensional spatial attitude parameters of the hull, perform time-discrete differential update. Smooth the matrix elements of continuous sampling periods to suppress abrupt attitude jumps caused by water wave disturbances, obtaining a continuous and stable direction cosine transformation matrix from the hull carrier coordinate system to the horizontal reference system. Specifically, this includes: performing time-discrete differential update calculations based on the reference direction cosine transformation matrix and the rate of change of angular velocity in the real-time three-dimensional spatial attitude parameters of the hull. The differential update calculation is based on the small-angle rotation approximation principle, using the attitude matrix and angular velocity data at the current moment to predict the attitude matrix at the next moment. The antisymmetric angular velocity matrix is ​​constructed from the three-axis angular velocity data in the real-time three-dimensional spatial attitude parameters of the hull, and its calculation satisfies the following formula: ; In the formula: The angular velocity antisymmetric matrix, Let be the angular velocity of the ship's hull about the X-axis. Let be the angular velocity of the ship's hull about the Y-axis. Let be the angular velocity of the hull about the Z-axis. The time discretization differential update calculation satisfies the following formula: In the formula, The cosine transform matrix for the predicted direction at the next sampling time. This is the cosine transform matrix of the reference direction at the current sampling time. It is a third-order identity matrix. The angular velocity antisymmetric matrix, To ensure a fixed sampling time interval, trajectory smoothing is performed on matrix elements across consecutive sampling periods. A sliding window weighted average is used to calculate the matrix elements across multiple adjacent sampling periods. The sliding window contains data from the five most recent sampling periods, and different weights are assigned to the data within the window, with more recent data having a higher weight than older data. The weight coefficients are set to [0.4, 0.3, 0.15, 0.1, 0.05], and the sum of the weight coefficients is 1. The weighted average calculation satisfies the following formula: ; In the formula: The smoothed direction cosine transform matrix. For the first Weighting coefficients for data in each sampling period For the first The direction cosine transformation matrix at each sampling time is processed by re-orthogonal normalization and determinant sign verification of the matrix after each weighted average. The orthogonality of the matrix and the right-hand rule are preserved to ensure that the physical meaning of the transformation relationship remains unchanged. Finally, the direction cosine transformation matrix from the continuous and stable ship carrier coordinate system to the horizontal reference system of the water surface is obtained.

[0038] In this embodiment of the invention, a method for constructing a direction cosine transform matrix is ​​adopted, which involves a dual-coordinate system with a single reference definition, matrix cascading operations with a fixed rotation order, step-by-step iterative orthogonal normalization verification, and time-domain weighted sliding smoothing processing. This method leverages the hardware floating-point operation capability of the core MCU on the unmanned vessel's main control circuit board, the calibration data storage support of the parameter file storage card, the geographic reference provided by the satellite positioning module, and the remote data transmission capability of the network module. Furthermore, it combines an in-cabin temperature control and heat dissipation system to ensure stable operation. This overcomes the technical problems of inconsistent coordinate system definitions, ambiguous attitude calculations, cumulative non-orthogonal distortion in numerical calculations, and abrupt changes in attitude data caused by surface wave disturbances in existing unmanned measurement vessels. Consequently, a direction cosine transform matrix with clear physical meaning, satisfying orthogonal constraints, and continuous stability is obtained.

[0039] In a preferred embodiment of the present invention, step 2 above may include: Step 25: Based on the direction cosine transformation matrix, extract the real-time projection coordinates of the water surface normal unit vector in the ship's hull coordinate system; based on the real-time projection coordinates, perform spatial geometric inverse kinematics calculations in conjunction with the initial mechanical zero-position deflection angle of the ultrasonic detector to obtain the spatial angle deviation between the detector target transmission axis and the current actual axis, and obtain the basic reverse compensation angle. Specifically, this includes: reading the direction cosine transformation matrix from the continuous and stable ship's hull coordinate system to the water surface horizontal reference system from the internal high-speed cache, and extracting the third column vector of the matrix, which corresponds to the Z-axis of the water surface horizontal reference system in the ship's hull coordinate system. The unit vector in the body coordinate system, namely the water surface normal unit vector, has three components that represent the projected coordinates of the water surface normal on the X-axis, Y-axis, and Z-axis of the ship's body coordinate system. The initial deflection angle parameter of the ultrasonic detector's mechanical zero position is retrieved from the parameter file storage card. This parameter is obtained by calibration on a horizontal calibration platform before the equipment leaves the factory and reflects the fixed angle deviation between the actual transmission axis and the theoretical zero position axis when the detector is installed. The parameter file storage card is installed near function area 4 of the main control circuit board and supports parameter reading and updating via a computer connected to the power supply interface.

[0040] The core MCU combines the real-time projected coordinates of the water surface normal unit vector with the initial deflection angle of the mechanical zero position to perform spatial geometric inverse calculation. The calculation process is completed by the hardware floating-point arithmetic unit in functional area 4 of the main control circuit board. The calculation result is stored in the dedicated cache area inside the core MCU. The spatial angle deviation between the detector target transmission axis and the current actual axis is calculated to obtain the basic reverse compensation angle. The basic reverse compensation angle represents the theoretical angle required to make the detector transmission axis perpendicular to the instantaneous water surface.

[0041] Step 26: Based on the basic reverse compensation angle, call the pre-calibrated transmission mechanism friction characteristic model and load mass distribution parameters to calculate the static friction torque threshold and Coulomb friction component of the rotating pair; based on the static friction torque threshold and Coulomb friction component of the rotating pair, determine the compensation amount used to offset the dead zone and low-speed crawling phenomenon of the mechanical transmission, and obtain the friction compensation angle increment. Specifically, this includes: based on the basic reverse compensation angle, calling the pre-calibrated transmission mechanism friction characteristic model and load mass distribution parameters in the parameter file storage card. The transmission mechanism friction characteristic model includes parameters such as the static friction coefficient, dynamic friction coefficient, and contact area of ​​the rotating pair; the load mass distribution parameters include parameters such as the mass of the ultrasonic detector body, the mass of the transmission gear, and the moment of inertia of each component. Both types of parameters are calibrated by dedicated testing equipment before the equipment leaves the factory. The core MCU calculates the static friction torque threshold and Coulomb friction component of the rotating pair based on the transmission mechanism friction characteristic model and load mass distribution parameters, and the calculation satisfies the formula: ; ; In the formula, The threshold value for static friction torque of the rotating pair. Let be the static friction coefficient of the rotating pair. For the normal force on the contact surface of the rotating pair, The equivalent radius of the rotating joint; Let Coulomb friction component, To determine the coefficient of friction of the rotating pair, the compensation amount used to offset the dead zone and low-speed crawling phenomenon of the mechanical transmission is determined based on the static friction torque threshold and the Coulomb friction component of the rotating pair. When the theoretical torque corresponding to the basic reverse compensation angle is less than the static friction torque threshold, the compensation amount is increased to make the output torque exceed the static friction torque threshold, thus overcoming the transmission dead zone. When the detector is rotating, the compensation amount corresponding to the Coulomb friction component is superimposed to suppress the low-speed crawling phenomenon. The above compensation amount is converted into an angle quantity to obtain the friction compensation angle increment.

[0042] Step 27: Based on the friction compensation angle increment, combined with the angular rate vector and submerged volume parameters of the detector during deflection in water, calculate the hydrodynamic damping torque and the additional mass inertial drag; based on the hydrodynamic damping torque and the additional mass inertial drag, solve for the feedforward compensation torque value through the inverse dynamic model; map the feedforward compensation torque value to an equivalent angle correction amount and superimpose it onto the friction compensation angle increment to obtain the dynamic feedforward adjustment amount. Specifically, this includes: the core MCU calculating the hydrodynamic damping torque and the additional mass inertial drag torque based on the friction compensation angle increment, combined with the angular rate vector and submerged volume parameters of the detector during deflection in water. The detector submerged volume parameters are pre-stored in the parameter file storage card, and the angular rate vector is extracted from the real-time three-dimensional spatial attitude parameters of the hull, and the calculation satisfies the following formula: , ; In the formula, This is the fluid dynamic damping torque. For water density, The detector drag coefficient, The detector's frontal area. The linear velocity at the edge of the detector. For the detector's equivalent arm; To add mass inertial drag torque, Add mass to the detector. To determine the angular acceleration of the detector, the core MCU, based on the fundamental laws of rigid body rotational dynamics and combined with the force characteristics of the underwater rotational system, establishes an inverse dynamic model of the detector's rotational system. The model is as follows: the total moment of inertia of the underwater rotational system comprises two parts: the inherent moment of inertia of the detector body, rotating support, and transmission mechanism; and the additional moment of inertia generated by the synchronous movement of the water body with the detector. The inherent moment of inertia is calibrated using a moment of inertia tester before the equipment leaves the factory and stored in the parameter file memory card. The additional moment of inertia is calculated by multiplying the additional mass by the square of the equivalent force arm, and its calculation satisfies the following formula: ; In the formula: To account for the additional moment of inertia, all other parameters remain consistent with the aforementioned formula. The total moment of inertia is the sum of the inherent moment of inertia and the additional moment of inertia, and its calculation satisfies the following formula: In the formula, The total moment of inertia of the system. The inherent moment of inertia of the detector rotation system is given. The torques experienced by the detector during rotation include the driving torque output by the servo motor, the frictional resistance torque of the rotating pair, the fluid dynamic damping torque, and the additional mass inertial resistance torque. The frictional resistance torque is calculated in step 26, while the fluid dynamic damping torque and the additional mass inertial resistance torque are calculated using the aforementioned formulas. All resistance torques are in the opposite direction to the detector's rotation. According to the fundamental laws of rigid body rotational dynamics, the net external torque of the system is equal to the product of the total moment of inertia and the angular acceleration. The net external torque is the driving torque minus the sum of all resistance torques, and its equation is as follows: ; In the formula: To provide driving torque for the servo motor. To determine the frictional resistance torque of the rotating pair, while keeping the other parameters consistent with the aforementioned formula, an algebraic transformation is performed on the forward dynamic model equations. The driving torque is moved to the left side of the equations, and the remaining terms are moved to the right side. This yields the corresponding relationships between the driving torque, angular acceleration, and various resistance torques, which constitutes the inverse dynamic model. Its calculation satisfies the following formula: ; The core MCU calculates the desired angular acceleration required for the detector to reach the target angle based on the friction compensation angle increment and the system's fixed control cycle. Substituting the desired angular acceleration and the calculated drag torques into the inverse dynamic model equations, it solves for the feedforward compensation torque value. This feedforward compensation torque is the servo output torque required to make the detector rotate smoothly at the desired angular acceleration. The core MCU calls a pre-stored servo torque-angle calibration mapping table in the parameter file storage card to map the feedforward compensation torque value into an equivalent angle correction. This mapping table was obtained through servo bench calibration experiments, recording the equivalent angle changes corresponding to different output torques. The core MCU then adds the equivalent angle correction to the friction compensation angle increment to obtain the dynamic feedforward adjustment. During the calculation, an onboard thermometer continuously collects the cabin air temperature at a 100ms cycle. When the temperature exceeds 45 degrees Celsius, the cooling fan automatically starts, circulating air through the core MCU, the step-down module, and the satellite positioning module to maintain the component operating temperature within the normal range. When the temperature drops below 40 degrees Celsius, the cooling fan automatically stops running.

[0043] Step 28: Perform closed-loop deviation integration on the dynamic feedforward adjustment and the real-time acquired servo encoder feedback angle to obtain a pulse width modulation duty cycle control signal; perform electrical isolation and power drive stage conversion on the pulse width modulation duty cycle control signal to obtain a servo drive pulse sequence with inertia adaptive adjustment characteristics. Specifically, this includes: performing closed-loop deviation integration on the dynamic feedforward adjustment and the real-time acquired servo encoder feedback angle to obtain a pulse width modulation duty cycle control signal; outputting the pulse width modulation duty cycle control signal to the electrical isolation circuit of the main control circuit board. The electrical isolation circuit uses opto-isolation devices to isolate the control signal from the power drive signal. The circuit blocks electromagnetic interference from the high-current loop to the core MCU. The isolated control signal is input to the power drive stage circuit, which consists of MOSFETs and provides high-power drive current for the servo motor. The power drive stage circuit performs power-level conversion on the electrically isolated control signal to generate a servo motor drive pulse sequence with inertia adaptive adjustment characteristics. The core adjustment objects of the drive pulse sequence are the pulse width and pulse output frequency. These two parameters can be autonomously adjusted according to the real-time rotational inertia of the ultrasonic detector and the changes in underwater load resistance. The entire adaptive adjustment logic is implemented by a preset mapping function, with no fixed constant parameter output, adapting to complex water load fluctuation conditions.

[0044] The system acquires real-time operating current and angular acceleration data of the servo motor, and calculates the detector's current equivalent moment of inertia and real-time load torque in real time. The equivalent moment of inertia is obtained by superimposing the detector's inherent mechanical inertia and the underwater added mass inertia. The real-time load torque includes mechanical friction torque and underwater fluid damping torque. The system uses a pre-defined mapping function between pulse width, pulse frequency, and load parameters to achieve adaptive matching. The formula for adaptive pulse width adjustment is as follows: ; In the formula, To adaptively adjust the real-time pulse width, To calibrate the reference pulse width for the equipment, This represents the current total equivalent moment of inertia of the detector. To calibrate the reference moment of inertia of the detector under no-load conditions, This represents the current real-time load torque. The formula for adaptive adjustment of pulse output frequency is as follows: (Based on rated load torque) ; In the formula, To adaptively adjust the real-time pulse output frequency, To calibrate the reference pulse frequency for the equipment, all other parameters remain consistent with the above formula. When the detector is under underwater high load and high inertia deflection conditions, the drive pulse width increases synchronously and the pulse frequency decreases synchronously to increase the servo drive torque and ensure smooth output of deflection action. When the detector is under low load and low inertia deflection conditions, the drive pulse width decreases synchronously and the pulse frequency increases synchronously to improve the servo response speed. The entire adaptive mapping relationship is pre-fixed to the parameter file storage card through a water tank calibration experiment. Each control cycle completes a parameter iteration update to ensure that the drive pulse sequence is completely matched with the real-time load conditions. The final inertia adaptive drive pulse sequence is transmitted to the servo through a dedicated interface.

[0045] In a preferred embodiment of the present invention, step 3 above may include: Step 31: Based on the servo drive pulse sequence, control the power drive circuit to generate phase current excitation; based on the phase current excitation, drive the ultrasonic detector to perform deflection motion along a preset mechanical rotation axis; during the deflection motion, read the feedback signal from the built-in encoder in real time to obtain the actual angular displacement data of the detector, specifically including: reading the servo drive pulse sequence with inertia adaptive adjustment characteristics from the internal high-speed cache, the frequency of the pulse sequence is 50Hz, the pulse width range is 1ms to 2ms, corresponding to the rotation range of the servo motor from 0 degrees to 180 degrees, and outputting the servo drive pulse sequence to the power drive circuit of the main control circuit board. The power drive circuit is equipped with an electrical isolation unit at the front end, using high-speed opto-isolation. The device achieves electrical isolation between control and power signals, blocking interference from high-current loops to the core control circuit. The electrically isolated pulse signal is input to an H-bridge power drive stage composed of N-channel enhancement-mode MOSFETs. The power drive stage converts the pulse signal into a three-phase current excitation with corresponding amplitude and frequency. This three-phase current excitation is transmitted to the stator winding of the servo motor via a shielded dedicated cable, generating a rotating magnetic field that drives the servo motor rotor. The servo motor output shaft is connected to the rotating bracket of the ultrasonic detector via a two-stage reduction gear transmission mechanism with a transmission ratio of 120:1. The rotating bracket is made of aluminum alloy with an anodized surface for corrosion resistance. The ultrasonic detector is fixed to the end of the rotating bracket and rotates synchronously with it. The preset mechanical rotation axis is parallel to the ship's transverse axis. This axis position is calibrated using a three-dimensional coordinate measuring machine before the equipment leaves the factory, with a calibration accuracy of 0.05 degrees.

[0046] The ultrasonic detector incorporates a 16-bit absolute photoelectric encoder, mounted at the end of the servo motor's output shaft and rotating coaxially with it. The encoder uses Gray code output to prevent jump errors during data transmission. The encoder acquires real-time angular displacement data from the detector, with a resolution of 0.01 degrees. The acquired angular data is transmitted to the core MCU via the unmanned surface vessel's external module communication bus interface, with a transmission cycle consistent with the system control cycle of 20ms. During data transmission, the CRC checksum of the data frame is verified in real time; frames with erroneous checksums are discarded and retransmissions are requested. During operation, an onboard thermometer continuously collects the cabin air temperature at 100ms intervals. When the temperature exceeds 45 degrees Celsius, the cooling fan automatically starts. The cooling fan uses a brushless DC motor with a speed of 3000 rpm. The cooling fan circulates air within the cabin through the core MCU, the step-down module, and the satellite positioning module, maintaining the component operating temperature within the normal range. When the temperature drops below 40 degrees Celsius, the cooling fan automatically stops operating.

[0047] Step 32: Based on the actual angular displacement data of the detector, extract the real-time angular value of the current control cycle; perform a subtraction operation on the real-time angular value and the reverse compensation angular value to obtain the angle tracking deviation value; perform an integral accumulation operation on the angle tracking deviation value to obtain the deviation integral correction amount. Specifically, this includes: extracting the real-time angular value of the detector in the current control cycle from the received encoder feedback data; performing a subtraction operation on the real-time angular value and the reverse compensation angular value to obtain the angle tracking deviation value. The angle tracking deviation value represents the angular difference between the actual position of the detector and the target position. When the deviation value is positive, the detector needs to rotate in the positive direction; when the deviation value is negative, the detector needs to rotate in the negative direction. Perform an integral accumulation operation on the angle tracking deviation value to obtain the deviation integral correction amount. The integral operation can eliminate the steady-state error of the system and improve the control accuracy. The calculation satisfies the following formula: ; ; In the formula, This represents the angle tracking deviation value. To compensate for the angle in the opposite direction, This represents the real-time rotation angle value of the detector. This is the integral correction amount for the deviation in the current control cycle. This is the integral correction amount for the deviation from the previous control cycle. The integral coefficient is... To maintain a fixed control cycle, the integral coefficients are pre-stored in the parameter file storage card and can be remotely adjusted via ground station software. The integral coefficients are obtained through water tank experiments. During the calibration process, the system's response speed and steady-state error under different integral coefficients are recorded, and the optimal value is selected as the default parameter. When the angle tracking deviation exceeds the preset maximum deviation threshold, the core MCU resets the integrator and clears the integral correction value to zero. The preset maximum deviation threshold is set to 5 degrees, and this threshold can be adjusted according to the actual operating conditions.

[0048] Step 33: Based on the deviation integral correction amount and combined with the dynamic change trend of the roll and pitch angles in the real-time three-dimensional spatial attitude parameters of the hull, construct a torque dynamic adjustment mapping relationship; based on the torque dynamic adjustment mapping relationship, correct the electromagnetic torque command of the servo shaft, compensate for the nonlinear disturbances caused by water flow impact load and mechanical transmission clearance, and obtain the compensated electromagnetic torque command, specifically including: the core MCU retrieves the pre-calibrated torque adjustment mapping table in the parameter file storage card. This mapping table is a two-dimensional lookup table structure. The row index corresponds to the attitude change rate, and the column index corresponds to the deviation integral correction. The elements in the table are the corresponding torque correction coefficients. The attitude change rate ranges from 0 degrees / second to 50 degrees / second, with a step size of 5 degrees / second; the deviation integral correction ranges from -5 degrees to +5 degrees, with a step size of 0.5 degrees. The calibration process of the mapping table is as follows: In a water tank test environment, simulate operating conditions with different water flow speeds and wave heights, collect data on the hull attitude change rate, deviation integral correction, and servo motor output torque. Perform statistical analysis on the collected data, calculate the optimal torque correction coefficient under different combinations of attitude change rates and deviation integral corrections, so that the system response speed and steady-state error are balanced. Fill the calculated optimal torque correction coefficient into the two-dimensional lookup table to generate the final torque adjustment mapping table, which is stored in the parameter file storage card. In the absence of water tank test conditions, a simplified analytical formula can be used as an alternative. The calculation of the torque correction coefficient satisfies the following formula: ; In the formula, This is the torque correction factor. This is the attitude change rate correction factor, with a default value of 0.02 s / degree. The rate of change of the ship's attitude. This is the correction factor for the integral deviation correction; the default value is 0.1 / degree. For the deviation integral correction, the core MCU inputs the current deviation integral correction and attitude change rate into a mapping table, and obtains the corresponding torque correction coefficient through bilinear interpolation. The core MCU then multiplies the torque correction coefficient by the original electromagnetic torque command to obtain the corrected electromagnetic torque command. The corrected electromagnetic torque command can compensate for nonlinear disturbances caused by water flow impact loads and mechanical transmission clearances. When the ship's attitude changes rapidly, the core MCU increases the electromagnetic torque command to improve the servo motor's response speed; when the detector approaches the target position, the core MCU decreases the electromagnetic torque command.

[0049] Step 34: According to the compensated electromagnetic torque command, continuously drive the ultrasonic detector to deflect, and monitor the pointing vector of the main lobe axis of the transmitted beam in space in real time; perform closed-loop feedback iterative control on the angle between the pointing vector and the instantaneous water surface normal direction, so that the angle converges to a preset tolerance range, and obtain the beam orthogonal locking state indicator. Specifically, this includes: according to the compensated electromagnetic torque command, continuously adjust the output current of the power drive circuit to drive the ultrasonic detector to deflect towards the target position, and calculate the pointing vector of the main lobe axis of the transmitted beam in space in real time. The pointing vector is calculated by using the direction cosine transformation matrix and the current rotation angle value of the detector. The theoretical pointing of the main lobe axis of the transmitted beam coincides with the mechanical axis of the ultrasonic detector. Compare the pointing vector of the main lobe axis of the transmitted beam with the vector of the instantaneous water surface normal direction, and calculate the spatial angle between the two. The vector of the instantaneous water surface normal direction is determined by the third column vector of the direction cosine transformation matrix. Perform closed-loop feedback iterative control on this angle, continuously adjust the output torque of the servo motor, so that the angle gradually decreases. The iterative control cycle is consistent with the system control cycle, and is adjusted once every 20ms.

[0050] When the included angle converges to within the preset tolerance range, a beam orthogonality lock status indicator is generated. The preset tolerance range is set to 0.1 degrees, which can be adjusted according to measurement accuracy requirements. The beam orthogonality lock status indicator is stored in an internal dedicated buffer and simultaneously transmitted to the ground station via the network module. After receiving the indicator, the ground station illuminates a green lock indicator light on the display interface to provide a status prompt to the operator. In the beam orthogonality lock state, changes in the included angle are continuously monitored. When the included angle exceeds the preset tolerance range, the lock state is automatically released, and the beam orthogonality adjustment process is re-executed. Relevant data on the lock state include lock time, maximum included angle during the lock period, and average included angle.

[0051] In this embodiment of the invention, a multi-level collaborative control method is adopted, which combines closed-loop angle control with real-time encoder feedback, torque adaptive adjustment based on dynamic changes in hull attitude, and real-time monitoring and orthogonal locking of beam pointing vector. This method relies on the electrical isolation power drive circuit of the unmanned vessel's main control circuit board, the real-time computing power of the core MCU, the calibration data storage support of the parameter file storage card, and the remote status transmission capability of the network module. At the same time, the in-cabin temperature control and heat dissipation system ensures stable hardware operation. Therefore, the technical problems of existing unmanned measurement vessel servo control being susceptible to water flow impact disturbances, mechanical transmission gaps causing control lag, and unstable beam pointing are overcome. This enables the ultrasonic detector's emitted beam main lobe axis to be continuously orthogonal to the instantaneous water surface.

[0052] In a preferred embodiment of the present invention, step 3 above may include: Step 35: Based on the beam orthogonal locking status indicator, control the ultrasonic detector to emit a detection acoustic pulse; after the detection acoustic pulse is emitted, activate the echo reception acquisition channel to acquire the underwater reflected echo signal; perform bandpass filtering and envelope detection processing on the underwater reflected echo signal to obtain the processed echo signal; extract the round-trip time difference of the sound wave based on the processed echo signal; calculate the slant range propagation path length of the sound wave based on the round-trip time difference of the sound wave and the preset water sound velocity parameters. Specifically, this includes: after detecting the beam orthogonal locking status indicator, sending a transmission trigger command to the ultrasonic detector; the beam orthogonal locking status indicator is stored inside the core MCU. In the dedicated status register, a register bit of 1 indicates that the lock is active, and a bit of 0 indicates that the lock is deactivated. The ultrasonic detector, fixed to the end of the rotating bracket, is made of piezoelectric ceramic material, operates at a frequency of 200kHz, has a transmission power of 100W, and a beam angle of 3 degrees. The transducer is connected to the ultrasonic detection circuit on the main control circuit board via a waterproof cable. The cable is 1.5 meters long and covered with a polyurethane sheath, providing waterproof and corrosion-resistant properties. After receiving the trigger command, the transducer transmits a detection acoustic pulse with a duration of 50μs. The detection acoustic pulse propagates vertically downwards along the main lobe axis of the transmission beam and is reflected upon encountering underwater terrain or obstacles, resulting in an underwater reflected echo signal. After the detection acoustic pulse is transmitted, the transmitting circuit is immediately shut down, and the receiving echo acquisition channel is turned on to prevent the transmitted signal from directly entering the receiving circuit and causing saturation. The acquisition channel uses a 16-bit successive approximation analog-to-digital converter with a sampling rate of 1MHz and an input voltage range of -5V to +5V.

[0053] The acquired raw echo signal first enters an active bandpass filter circuit. This bandpass filter uses a fourth-order Butterworth filter structure with a passband range of 180kHz to 220kHz, a passband ripple of less than 0.5dB, and a stopband attenuation greater than 40dB. The bandpass filter removes out-of-band interference signals such as motor electromagnetic interference and water flow noise. The filtered signal is then input to a peak envelope detection circuit. This circuit uses a combination of diode detection and RC low-pass filtering to extract the amplitude envelope of the echo signal, resulting in the processed echo signal. The core MCU performs adaptive threshold detection on the processed echo signal. The detection threshold is dynamically adjusted based on the background noise level. When the echo signal amplitude exceeds the current detection threshold, the core MCU records the echo arrival time with a time resolution of 1μs. The difference between the sound pulse emission time and the echo arrival time is calculated to obtain the round-trip propagation time difference. Based on the round-trip propagation time difference and preset water velocity parameters, the slant range propagation path length is calculated, satisfying the following formula: ; In the formula, The slant range of the sound wave is the path length. To preset the water sound velocity parameters, The default value for the water body sound velocity parameter is 1500m / s, which is set to the round-trip time difference of sound wave propagation. It can be adjusted by ground station software according to the temperature, salinity and depth of the operating water area. The sound wave slant range propagation path length data is stored in the dedicated buffer area inside the core MCU and is also transferred to the parameter file storage card for local storage. The storage format is binary file, and each data contains three fields: timestamp, slant range value and sound velocity value.

[0054] Step 36: Based on the acoustic wave slant range propagation path length, and combined with the residual roll and pitch components in the real-time three-dimensional spatial attitude parameters of the hull, construct a geometric projection model coupling water surface wave undulation and hull tilt. Based on the geometric projection model, remove the acoustic path geometric distortion component caused by the instantaneous non-horizontal state of the water surface to obtain the corrected effective acoustic path data. Specifically, this includes: extracting the residual roll and pitch components of the current measurement cycle from the real-time three-dimensional spatial attitude parameters of the hull. The residual roll and pitch components represent the slight fluctuation deviations in the hull attitude under beam-orthogonal locking. These slight angular deviations are difficult to eliminate through mechanical deflection compensation by the servo motor and are generated by micro-wave disturbances on the water surface and weak mechanical vibrations of the hull. They belong to the instantaneous local slight tilt deviations of the water surface, and the angular amplitude is always maintained in a very small range. Combined with the acoustic wave slant range propagation path length, construct a geometric projection model coupling water surface wave undulation and residual slight tilt of the hull. This model is specifically designed to correct the acoustic path geometric distortion caused by the residual minute attitude deviation after the servo motor has fully compensated for a large-angle tilt. It is effective for instantaneous local micro-tilt scenarios on the water surface and does not involve correction of large-angle attitude deviations of the entire hull. The core MCU, based on the geometric projection model, removes the acoustic path geometric distortion component caused by the minute non-horizontal state of the instantaneous water surface, corrects the residual deviation of the beam pointing, and obtains the corrected effective acoustic path data, which is calculated according to the following formula: ; ; In the formula, The total beam tilt angle caused by residual attitude deviation; These are the residual roll component and the residual pitch component. Original acoustic wave slant range propagation path length; To correct the effective sound path data, the influence of minor attitude residual deviations after beam orthogonal locking is eliminated. The data reference is the instantaneous tilted water surface after servo compensation. Measurement errors caused by micro-wave undulations are eliminated, and the macroscopic sound path offset corresponding to the overall tilt of the hull is retained.

[0055] Step 37: Based on the corrected effective sound path data, and using the reverse compensation angle as the kinematic compensation reference, perform an inverse spatial coordinate transformation on the sound wave propagation path, projecting the slant distance onto the normal axis perpendicular to the water surface to obtain the normal axis projection result. Specifically, this includes: based on the reverse compensation angle, which is the large angle compensation amount for the overall tilt of the hull, representing the macroscopic tilt angle of the hull's coordinate system relative to the stationary standard water surface, and using the reverse compensation angle as the kinematic compensation reference, perform an inverse spatial coordinate transformation on the corrected effective sound path data. The core function of this inverse spatial coordinate transformation is to unify the reference, projecting the sound path data based on the instantaneously tilted water surface onto the standard normal axis perpendicular to the stationary water surface, eliminating the reference offset problem caused by the overall tilt of the hull. Combining the objective laws of spatial geometric projection, the spatial projection conversion calculation satisfies the following formula: ; ; In the formula, The total reverse compensation angle is the sum of the roll compensation angle and the pitch compensation angle. , The reverse compensation angle in the roll and pitch directions; For the final normal axis projection result, when the ship tilts as a whole, the ultrasonic detector beam is always perpendicular to the instantaneous water surface after being compensated by the servo motor. At this time, the beam propagation slant range is greater than the actual vertical water depth. Through cosine multiplication projection conversion, the tilt slant range can be accurately converted into standard vertical water depth data. The larger the tilt angle of the ship, the larger the projection correction. The entire inverse coordinate transformation is completed by the floating-point arithmetic unit inside the core MCU with high-precision iterative processing. The calculation process retains all data precision and resolution and does not produce additional numerical distortion. The converted normal axis projection result is uniformly stored in the high-speed cache area inside the core MCU.

[0056] Step 38: Based on the normal axis projection result, depth data smoothing filtering is performed in conjunction with the water body sound velocity distribution gradient characteristics to remove abnormal jump values ​​caused by surface foam and underwater suspended matter, thus obtaining vertical water depth data. Specifically, this includes: combining the water body sound velocity distribution gradient characteristics to perform depth data smoothing filtering on the normal axis projection result. The water body sound velocity distribution gradient characteristics are determined by the temperature stratification, salinity stratification, and pressure stratification of the operating water area, resulting in differences in sound velocity at different depths, which in turn causes depth measurement errors. A sliding window weighted average method is used to process the depth data of multiple consecutive measurement cycles. The sliding window contains the data of the most recent 5 measurement cycles, and the weight coefficients are set to [0.4, 0.3, 0.15, 0.1, 0.05]. The smoothing filtering process suppresses the depth data fluctuations caused by the sound velocity gradient and retains the true changes in underwater topography. The core MCU performs outlier removal processing on the filtered depth data. By comparing the difference between the current data and adjacent data, when the difference exceeds the preset outlier threshold, the data is determined to be an abnormal jump value. Abnormal outliers are typically caused by factors such as surface foam, underwater suspended matter, fish movement, and bubble interference. The preset outlier threshold is set to 1 meter, which can be adjusted according to the actual operating environment. After removing abnormal outliers, linear interpolation is used to fill in the gaps with adjacent valid data to ensure the continuity of the data sequence.

[0057] After the above processing, the final vertical water depth data is obtained. The vertical water depth data represents the vertical distance from the bottom of the water to the still water surface, with a data resolution of 0.01 meters. This data is stored in real time in the parameter file storage card in CSV file format. Each data entry contains four fields: timestamp, longitude, latitude, and water depth value. At the same time, the data is transmitted to the ground station through the network module using the TCP / IP protocol. CRC check is performed during data transmission to ensure the integrity of the data transmission. After receiving the data, the ground station plots the water depth change curve in real time to obtain an underwater topographic profile. During the calculation, the onboard thermometer continuously collects the air temperature inside the chamber at a period of 100ms. When the temperature exceeds 45 degrees Celsius, the cooling fan automatically starts. The cooling fan uses a DC brushless motor with a speed of 3000 rpm. The cooling fan circulates the air inside the chamber through the core MCU, the step-down module, and the ultrasonic detection circuit to maintain the operating temperature of the components within the normal range. When the temperature drops below 40 degrees Celsius, the cooling fan automatically stops running.

[0058] In this embodiment of the invention, a multi-stage water depth measurement data processing method is adopted, which involves beam orthogonal locking trigger detection, active bandpass filtering and peak envelope detection echo signal processing, water surface tilt geometric distortion removal, inverse spatial coordinate transformation and depth data smoothing filtering. This method relies on the real-time computing power of the core MCU of the unmanned vessel's main control circuit board, the local data storage support of the parameter file storage card, and the remote data transmission capability of the network module. At the same time, it combines the cabin temperature control and heat dissipation system to ensure stable hardware operation. Therefore, it overcomes the technical problems of existing unmanned measurement vessels, such as the susceptibility of echo signals to interference, water surface tilt causing sound path measurement distortion, residual errors in hull attitude affecting depth accuracy, and abnormal data interfering with measurement results. This results in accurate vertical water depth data based on a static water surface reference.

[0059] like Figure 2 As shown, embodiments of the present invention also provide an unmanned measurement vessel control system based on attitude adaptive compensation, including: The acquisition module is used to receive attitude compensation measurement trigger signals; based on the attitude compensation measurement trigger signals, it acquires the original angular rate and linear acceleration data of the hull in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, it obtains the real-time three-dimensional spatial attitude parameters of the hull. The module is used to construct the direction cosine transformation matrix from the ship's carrier coordinate system to the horizontal reference system of the water surface based on the real-time three-dimensional spatial attitude parameters of the ship; according to the direction cosine transformation matrix, the reverse compensation angle required for the ultrasonic detector to maintain normal emission is calculated; according to the reverse compensation angle, dynamic feedforward compensation is performed in combination with the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to obtain the servo drive pulse sequence. The correction module is used to drive the ultrasonic detector to perform deflection actions based on the servo drive pulse sequence and to collect the actual angular displacement of the ultrasonic detector in real time; to perform deviation integral correction based on the actual angular displacement and the reverse compensation angle, and to dynamically adjust the ultrasonic detector so that the main lobe axis of the transmitted beam is continuously orthogonal to the instantaneous water surface; to receive the underwater acoustic wave reflection echo and remove the acoustic path geometric distortion caused by the hull tilt, and to perform kinematic compensation correction on the slant range propagation path of the acoustic wave using the reverse compensation angle to obtain the vertical water depth data.

[0060] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0061] like Figure 3As shown, in a specific embodiment of the unmanned survey vessel control circuit board based on attitude adaptive compensation, the circuit board includes an MCU 5. The MCU 5 receives a stable 3.3V operating voltage provided by the first step-down module 4 to implement the aforementioned attitude adaptive compensation unmanned survey vessel control method. The right side area of ​​the MCU 5 integrates an RS232 to TTL level conversion circuit and a microcontroller power supply circuit. The level conversion circuit enables level-compatible communication with external serial devices.

[0062] Specifically, the circuit board also includes: A backup lithium battery 8 is encapsulated within a white casing. When the main battery pack of the unmanned vessel is not powered on, the backup lithium battery 8 outputs its voltage, which is then boosted by a boost circuit to the operating voltage required by the 433MHz receiver module, providing continuous power to the receiver. The boost circuit employs a DC-DC boost topology to raise the nominal voltage of the lithium battery (e.g., 3.7V) to the 5V operating voltage required by the receiver.

[0063] The receiver (433 receiver module) is electrically connected to the boost circuit output of the backup lithium battery 8. When the operator presses a button on the remote control, the receiver receives the remote control signal from the remote control, verifies the remote control command through the internal decoding chip, and outputs a high-level signal. This high-level signal turns on the MOSFET switch of the unmanned vessel's main battery pack through the control chip, realizing the short-press power-on function. That is, when the duration of the high-level signal falls within the preset short-press effective duration range (e.g., 0.5s to 2s), the main battery pack is turned on. The long-press power-off function is realized when the duration of the high-level signal exceeds the preset long-press threshold (e.g., 3s), the MCU5 executes the power-off logic, cutting off the power supply to the main battery pack. After the main battery pack is turned on, the power supply of the receiver is switched from the backup lithium battery 8 to the main battery pack through a dual-power smooth switching circuit. The dual-power smooth switching circuit has a 200ms overlapping power supply window to avoid voltage drops during switching transients. Meanwhile, MCU 5 controls the charging circuit to charge the backup lithium battery 8: when the terminal voltage of the backup lithium battery 8 is lower than the pre-charge voltage threshold, a constant current pre-charge mode is executed; when the terminal voltage enters the constant current charging range, a constant current charging mode is executed; when the terminal voltage reaches the constant voltage charging cutoff voltage, a constant voltage charging mode is executed, until the charging current drops below the charging stop current, at which point charging is complete. During charging, the charging status indicator light illuminates; after charging is complete, the charging completion indicator light illuminates and the charging status indicator light turns off.

[0064] The delayed power-on module 9 has its input terminal electrically connected to the output terminal of the main battery pack, receiving the 12V DC voltage output by the main battery pack after power-on. The delayed power-on module 9 is equipped with a physical adjustment knob, allowing operators to physically set the delay time parameter (e.g., adjustable to 0.5s, 1s, and 2s). Based on the set delay time, the delayed power-on module 9 sequentially sends enable signals to the first step-down module 4, controlling the first step-down module 4 to start in stages with a delay, avoiding the instantaneous high current surge and power bus voltage drop caused by simultaneous power-on of all functional modules.

[0065] The first step-down module 4 has its enable terminal electrically connected to the output terminal of the delayed power-on module 9. Upon receiving the enable control signal from the delayed power-on module 9, the first step-down module 4 starts operating, converting the 12V DC voltage output from the main battery pack into stable operating voltages of different levels required by various functional modules. It provides 3.3V operating voltage to the MCU 5, 3.3V operating voltage to the satellite positioning module 10, and 3.3V operating voltage to the network module 3. The first step-down module 4 internally integrates multiple DC-DC step-down conversion circuits, and each output is equipped with a filter capacitor network to suppress power supply ripple.

[0066] The satellite positioning module 10 has its power supply terminal electrically connected to the output terminal of the first step-down module 4, and starts working after receiving 3.3V power from the first step-down module 4. The control terminal of the satellite positioning module 10 is electrically connected to the network module 3, and its working mode is directly controlled by the network module 3. The satellite positioning module 10 receives GNSS satellite navigation signals and has three output functions: first, it outputs centimeter-level positioning data, including longitude, latitude, and elevation information, through RTK real-time dynamic differential technology; second, it outputs ship heading angle information by performing carrier phase differential orientation calculation using a dual-antenna configuration; and third, it locks onto the satellite atomic clock time reference and outputs a high-precision UTC timestamp.

[0067] Network module 3 is bidirectionally connected to MCU 5 via communication bus interface 1. Network module 3 receives control commands from MCU 5 and processes the raw positioning, orientation, and timing data output by satellite positioning module 10, extracting RTK fixed solution status identifiers, latitude and longitude coordinates, heading angles, and UTC time information. Simultaneously, network module 3 also analyzes the attitude data output by the transducer attitude sensor to obtain the real-time attitude information of the ultrasonic detector underwater. Network module 3 transmits the analysis results back to MCU 5 via communication bus interface 1.

[0068] The parameter file storage module 2 is electrically connected to the SPI communication interface of the MCU 5, receiving read and write commands from the MCU 5. It stores the sensor's factory calibration parameters (including zero-bias calibration values ​​and temperature drift compensation coefficients), spatial coordinate transformation calibration parameters, transmission mechanism friction characteristic model parameters, and default parameters for water sound velocity. The parameter file storage module 2 also provides an external computer access channel via the communication bus interface 1. When necessary, technicians can connect to an external computer through the communication bus interface 1 to read, verify, and fine-tune the parameters stored in the parameter file storage module 2.

[0069] The navigation control module 12 is bidirectionally connected to the MCU 5 and network module 3 via the communication bus interface 1. The navigation control module 12 receives navigation control commands processed by the MCU 5 and positioning and orientation data parsed by the network module 3, and performs three tasks: First, based on the trajectory planning commands and real-time positioning and orientation data, combined with the ship's real-time three-dimensional spatial attitude parameters, it calculates the thruster speed and rudder angle control quantities to achieve autonomous navigation control; second, it receives and parses the detection data from the shipborne radar for target detection and tracking; third, it is responsible for bidirectional wireless data communication with the ground control station, uploading ship status and measurement data, and receiving navigation commands issued by the ground station.

[0070] Communication bus interface 1 has two independent interfaces, one for signal communication and the other for high-current power supply. The two interfaces are physically separated on the circuit board. One interface is dedicated to transmitting small signal communication data such as attitude measurement data, satellite positioning data, and depth sounder data, while the other interface independently handles the transmission of high-current power supply data, effectively preventing high-frequency electromagnetic interference from the power supply line from coupling to the signal bus.

[0071] Furthermore, the circuit board also includes: The cooling fan 6 is driven by a DC brushless motor. Its power supply terminal is electrically connected to the output terminal of the first step-down module 4. After receiving power from the first step-down module 4, it operates at a speed of 3000 rpm. The cooling fan 6 provides forced air cooling to the second step-down module 13 and the satellite positioning module 10, keeping the surface temperature of the components within a safe operating range. On the other hand, it forces the hot air emitted by high-heat-generating equipment such as the lithium battery pack protection board, the depth sounder host, and the power module in the middle compartment of the unmanned vessel, according to the airflow direction indicated by the arrow, to circulate. This allows the hot air inside the compartment to flow past the location of the onboard thermometer, enabling real-time monitoring of the compartment temperature.

[0072] A power supply interface 11, located at the edge of the circuit board, provides external power to the circuit board. The power supply interface 11 connects the 12V DC voltage from the main battery pack or external power source to the circuit board, which is then converted by the second step-down module 13 and distributed to various components. The second step-down module 13 is independent of the first step-down module 4, each undertaking the power supply task for different functional modules, thus achieving a decentralized power supply circuit design.

[0073] The indicator light circuit board 7 is connected to the main control circuit board via an FPC flexible printed circuit cable. The indicator light circuit board 7 is equipped with a hull indicator light socket for connecting to an external LED indicator light module. The indicator light circuit board 7 receives status signals from the MCU 5 via the communication bus interface 1, driving multiple LED indicators to indicate the following five functional states: satellite positioning RTK fixed solution status indication (distinguishing between single-point positioning, floating-point solution, and fixed solution states, each displayed with a different colored LED), network differential signal reception status indication, depth sounder data parsing ready status indication, battery pack charging / discharging status indication (indicating charging in progress and charging complete states with charging status indicators and charging complete indicators respectively), and data storage status indication (distinguishing between writing in progress and idle states with different flashing frequencies).

[0074] In the above embodiment, the cooling fan 6 and the onboard thermometer form a closed-loop temperature control system: when the onboard thermometer detects that the cabin air temperature exceeds 45°C, the MCU 5 automatically starts the cooling fan 6 for forced cooling; when the temperature drops below 40°C, the MCU 5 controls the cooling fan 6 to automatically stop operating to save energy. A small connector is provided next to the cooling fan 6, which connects to the ship's wireless control switch. When the unmanned vessel is not used for a long period, the operator can manually turn off the switch to cut off the discharge circuit of the backup lithium battery 8, completely stopping the overall circuit function and preventing damage from excessive battery discharge.

[0075] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A control method for an unmanned survey vessel based on attitude adaptive compensation, characterized in that, The method includes: Step 1: Receive the attitude compensation measurement trigger signal; based on the attitude compensation measurement trigger signal, collect the original angular rate and linear acceleration data of the hull in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, obtain the real-time three-dimensional spatial attitude parameters of the hull. Step 2: Based on the real-time three-dimensional spatial attitude parameters of the hull, construct the direction cosine transformation matrix from the hull carrier coordinate system to the horizontal reference system of the water surface; according to the direction cosine transformation matrix, calculate the reverse compensation angle required for the ultrasonic detector to maintain normal emission; according to the reverse compensation angle, combine the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to perform dynamic feedforward compensation, and obtain the servo drive pulse sequence. Step 3: Drive the ultrasonic detector to perform deflection action based on the servo motor driven pulse sequence, and collect the actual rotation angle displacement of the ultrasonic detector in real time; perform deviation integral correction based on the actual rotation angle displacement and the reverse compensation angle, and dynamically adjust the ultrasonic detector to keep the main lobe axis of the transmitted beam continuously orthogonal to the instantaneous water surface; receive the underwater sound wave reflection echo and remove the sound path geometric distortion caused by the hull tilt, and use the reverse compensation angle to perform kinematic compensation correction on the sound wave slant range propagation path to obtain vertical water depth data.

2. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 1, characterized in that, The process of generating the attitude compensation measurement trigger signal includes: Obtain the remote control command verification signal, perform command encoding verification and key duration dual threshold judgment on the remote control command verification signal, and after the verification is passed, execute the main battery pack conduction and dual power supply smooth switching to obtain the power-on ready status indicator. Using the power-on ready status flag as the enabling condition, the device enters a low-power monitoring mode. After completing the communication bus initialization and power supply configuration of each sensor, the device collaborative operation benchmark is obtained. Using the equipment's collaborative operation benchmark as the working rhythm, the terminal voltage and charging current of the backup lithium battery are periodically collected, and the collected data is matched with the preset charging control mode to generate a power closed-loop management command. Based on the power closed-loop management command, it is confirmed that the backup lithium battery charging state and the main battery pack power supply state have entered the steady-state operation range. After the dual-path steady-state conditions of the power supply are met, a full-system measurement ready trigger command is sent to the attitude measurement and ultrasonic detection related sensors to generate an attitude compensation measurement trigger signal.

3. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 2, characterized in that, Step 1 includes: Receive the attitude compensation measurement trigger signal; according to the attitude compensation measurement trigger signal, acquire the original angular rate of the three-axis gyroscope and the original linear acceleration of the three-axis accelerometer of the inertial measurement unit; perform zero bias calibration and temperature drift compensation on the original angular rate and original linear acceleration to obtain calibrated inertial measurement data; Multi-band adaptive filtering is applied to the calibrated inertial measurement data to suppress high-frequency vibration noise and smooth the convergence of low-frequency attitude trends, resulting in filtered angular velocity data and filtered linear acceleration data. Based on the filtered linear acceleration data, the quasi-static gravitational acceleration projection component is extracted, and the filtered kinematic feature data is jointly constructed by the filtered angular velocity data and the quasi-static gravitational acceleration projection component. The filtered kinematic feature data is subjected to a three-axis orthogonal rotation mapping to obtain the coordinate mapping relationship from the sensor coordinate system to the hull structure reference coordinate system; based on the coordinate mapping relationship, the sensor mounting coordinate system is transformed to the hull structure reference coordinate system to obtain the hull reference system measurement data; based on the hull reference system measurement data, the sensor mechanical offset error is corrected to align the main measurement axis with the hull pitch axis, roll axis, and vertical axis to obtain the hull alignment angular rate data; The ship's hull alignment rate data is used to perform discrete-time Euler integration based on the preset rigid body kinematics differential equations to obtain an initial attitude angle estimate. The integral cumulative drift error of the initial attitude angle estimate is corrected in real time according to the quasi-static gravitational acceleration projection component to obtain the initial roll angle and the initial pitch angle. The instantaneous angular acceleration is obtained by performing a differential operation on the angular rate change sequence corresponding to the initial roll angle and the initial pitch angle; based on the instantaneous angular acceleration, dynamic response compensation is performed in combination with the fluid dynamic damping characteristics and the moment of inertia distribution to obtain the compensated angle and the compensated angular rate; the compensated angle, the compensated angular rate and the instantaneous angular acceleration are fused to obtain the real-time three-dimensional spatial attitude parameters of the hull.

4. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 3, characterized in that, Step 2, based on the real-time three-dimensional spatial attitude parameters of the hull, construct the direction cosine transformation matrix from the hull carrier coordinate system to the horizontal reference system of the water surface, including: Based on the real-time three-dimensional spatial attitude parameters of the hull, the roll angle and pitch angle of the current sampling period are extracted; a hull carrier coordinate system is established with the rotation axis of the ultrasonic detector as the spatial origin, and a water surface horizontal reference system is established with a plane parallel to the still water surface as the reference. The hull carrier coordinate system and the water surface horizontal reference system together constitute a spatial coordinate system mapping relationship. Based on the spatial coordinate system mapping relationship and the roll angle, a rotational mapping is performed around the longitudinal axis of the hull to obtain a transverse rotation transformation submatrix; based on the spatial coordinate system mapping relationship and the pitch angle, a rotational mapping is performed around the transverse axis of the hull to obtain a longitudinal rotation transformation submatrix; the transverse rotation transformation submatrix and the longitudinal rotation transformation submatrix are subjected to cascaded multiplication operations according to the rotation order of the hull's spatial attitude to obtain an initial spatial mapping matrix; The initial spatial mapping matrix is ​​subjected to orthogonal normalization iteration and determinant sign verification to remove non-orthogonal distortion components caused by the accumulation of sensor numerical calculations, thereby obtaining a reference direction cosine transformation matrix that satisfies strict orthogonal constraints. Based on the reference direction cosine transformation matrix, and combined with the angular rate of change in the real-time three-dimensional spatial attitude parameters of the hull, time discretization differential update is performed. The matrix elements of the continuous sampling period are smoothed to suppress the attitude jump caused by water surface wave disturbance, and the direction cosine transformation matrix from the continuous and stable hull carrier coordinate system to the water surface horizontal reference system is obtained.

5. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 4, characterized in that, Based on the direction cosine transform matrix, calculate the reverse compensation angle required for the ultrasonic detector to maintain normal emission; Based on the reverse compensation angle, and combined with the static friction torque of the ultrasonic detector rotation, the load rotational inertia, and the fluid damping characteristics, dynamic feedforward compensation is performed to obtain the servo motor drive pulse sequence, including: Based on the direction cosine transformation matrix, the real-time projection coordinates of the water surface normal unit vector in the ship carrier coordinate system are extracted; based on the real-time projection coordinates, spatial geometric inverse calculation is performed in combination with the initial deflection angle of the ultrasonic detector's mechanical zero position to obtain the spatial angle deviation between the detector's target transmission axis and the current actual axis, and the basic reverse compensation rotation angle is obtained. Based on the aforementioned basic reverse compensation angle, the pre-calibrated transmission mechanism friction characteristic model and load mass distribution parameters are invoked to calculate the static friction torque threshold and Coulomb friction component of the rotating pair; based on the static friction torque threshold and Coulomb friction component of the rotating pair, the compensation amount used to offset the dead zone of the mechanical transmission and the low-speed crawling phenomenon is determined, and the friction compensation angle increment is obtained. Based on the friction compensation angle increment, combined with the angular rate vector and immersion volume parameters of the detector when deflecting in water, the fluid dynamic damping torque and the additional mass inertial drag are calculated; based on the fluid dynamic damping torque and the additional mass inertial drag, the feedforward compensation torque value is solved through the inverse dynamic model; the feedforward compensation torque value is mapped to an equivalent angle correction amount and superimposed on the friction compensation angle increment to obtain the dynamic feedforward adjustment amount; The dynamic feedforward adjustment and the real-time acquired servo encoder feedback angle are subjected to closed-loop deviation integration to obtain a pulse width modulation duty cycle control signal; the pulse width modulation duty cycle control signal is electrically isolated and converted by the power drive stage to obtain a servo drive pulse sequence with inertia adaptive adjustment characteristics.

6. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 5, characterized in that, Step 3: Drive the ultrasonic detector to perform a deflection action based on the servo motor-driven pulse sequence, and collect the actual angular displacement of the ultrasonic detector in real time; perform deviation integration correction based on the actual angular displacement and the reverse compensation angle, and dynamically adjust the ultrasonic detector to ensure that the main lobe axis of the transmitted beam is continuously orthogonal to the instantaneous water surface, including: According to the servo drive pulse sequence, the power drive circuit is controlled to generate phase current excitation; according to the phase current excitation, the ultrasonic detector is driven to perform deflection motion along a preset mechanical rotation axis; during the deflection motion, the feedback signal of the built-in encoder is read in real time to obtain the actual angular displacement data of the detector. Based on the actual rotational displacement data of the detector, the real-time rotational value of the current control cycle is extracted; the difference between the real-time rotational value and the reverse compensation rotational value is calculated to obtain the angle tracking deviation value; the angle tracking deviation value is integrated and accumulated to obtain the deviation integral correction amount. Based on the deviation integral correction amount, and combined with the dynamic change trend of the roll and pitch angles in the real-time three-dimensional spatial attitude parameters of the hull, a torque dynamic adjustment mapping relationship is constructed; based on the torque dynamic adjustment mapping relationship, the electromagnetic torque command of the servo shaft is corrected, and the nonlinear disturbances caused by the water flow impact load and mechanical transmission clearance are compensated to obtain the compensated electromagnetic torque command. According to the compensated electromagnetic torque command, the ultrasonic detector is continuously driven to deflect, and the pointing vector of the main lobe axis of the transmitted beam in space is monitored in real time. The angle between the pointing vector and the instantaneous water surface normal direction is controlled by closed-loop feedback to make the angle converge to the preset tolerance range, and the beam orthogonal locking state indicator is obtained.

7. The unmanned measurement vessel control method based on attitude adaptive compensation according to claim 6, characterized in that, The system receives underwater acoustic wave reflections and eliminates the acoustic path geometry distortion caused by the ship's tilt. It then uses a reverse compensation angle to perform kinematic compensation correction on the acoustic wave slant range propagation path, obtaining vertical water depth data, including: According to the beam orthogonal locking status indicator, the ultrasonic detector is controlled to emit a detection acoustic pulse; after the detection acoustic pulse is emitted, the echo reception acquisition channel is turned on to acquire the underwater reflected echo signal; the underwater reflected echo signal is subjected to bandpass filtering and envelope detection to obtain the processed echo signal; the round-trip time difference of the sound wave is extracted based on the processed echo signal; the slant range propagation path length of the sound wave is calculated based on the round-trip time difference of the sound wave and the preset water sound velocity parameter; Based on the slant range propagation path length of the sound wave, and combined with the residual roll and pitch components in the real-time three-dimensional spatial attitude parameters of the hull, a geometric projection model coupling water surface wave undulation and hull tilt is constructed; based on the geometric projection model, the sound path geometric distortion component caused by the instantaneous non-horizontal state of the water surface is removed to obtain the corrected effective sound path data. Based on the corrected effective sound path data, and using the reverse compensation angle as the kinematic compensation reference, an inverse spatial coordinate transformation is performed on the sound wave propagation path to project the slant range onto the normal axis perpendicular to the water surface, thus obtaining the normal axis projection result. Based on the projection results of the normal axis, and combined with the characteristics of the water body sound velocity distribution gradient, depth data smoothing filtering is performed to remove abnormal jump values ​​caused by surface foam and underwater suspended matter, thus obtaining vertical water depth data.

8. An unmanned survey vessel control system based on attitude adaptive compensation, wherein the system implements the method as described in any one of claims 1 to 7, characterized in that, include: The acquisition module is used to receive attitude compensation measurement trigger signals; Based on the attitude compensation measurement trigger signal, the original angular rate and linear acceleration data of the hull are collected in real time; based on the preset rigid body kinematic differential equations and the original angular rate and linear acceleration data, the real-time three-dimensional spatial attitude parameters of the hull are obtained. The module is used to construct the direction cosine transformation matrix from the ship's carrier coordinate system to the horizontal reference system of the water surface based on the real-time three-dimensional spatial attitude parameters of the ship; according to the direction cosine transformation matrix, the reverse compensation angle required for the ultrasonic detector to maintain normal emission is calculated; according to the reverse compensation angle, dynamic feedforward compensation is performed in combination with the static friction torque of the ultrasonic detector rotation, the load rotational inertia and fluid damping characteristics to obtain the servo drive pulse sequence. The correction module is used to drive the ultrasonic detector to perform deflection actions based on the servo drive pulse sequence and to collect the actual angular displacement of the ultrasonic detector in real time; to perform deviation integral correction based on the actual angular displacement and the reverse compensation angle, and to dynamically adjust the ultrasonic detector so that the main lobe axis of the transmitted beam is continuously orthogonal to the instantaneous water surface; to receive the underwater acoustic wave reflection echo and remove the acoustic path geometric distortion caused by the hull tilt, and to perform kinematic compensation correction on the slant range propagation path of the acoustic wave using the reverse compensation angle to obtain the vertical water depth data.

9. A control circuit board for an unmanned measurement vessel based on attitude adaptive compensation, comprising an MCU (5), receiving a stable operating voltage provided by a first step-down module (4), for implementing the method as described in any one of claims 1 to 7, characterized in that, Also includes: The backup lithium battery (8) is encapsulated inside a white shell. When the main battery pack of the unmanned vessel is not turned on, it outputs the battery voltage and then powers the receiver after being boosted by the boost circuit. The receiver receives the remote control signal sent by the remote controller and outputs a high-level signal, which turns on the main battery pack switch of the unmanned boat through the chip. After the main battery pack is turned on, the receiver switches to the main battery pack for power supply, and at the same time the charging circuit charges the backup lithium battery (8) and indicates the charging and stop status. The delayed power-on module (9) receives the voltage output by the main battery pack after it is powered on, sets the delay time through the physical adjustment knob, and controls the first step-down module (4) to power on in stages with delayed power-on; the first step-down module (4) starts after receiving the enable control of the delayed power-on module (9), converts the main battery pack voltage into the required working voltage, and supplies power to the MCU (5), satellite positioning module (10) and network module (3); The satellite positioning module (10) starts after receiving power from the first step-down module (4) and is directly controlled by the network module (3), outputting positioning, orientation and timing data; The network module (3) receives control commands from the MCU (5), analyzes the positioning, orientation and timing data output by the satellite positioning module (10), analyzes the transducer attitude sensor data, and sends the analysis results back to the MCU (5). The parameter file storage module (2) receives read and write instructions from the MCU (5) and connects to an external computer via the communication bus interface (1) to modify parameters; The navigation control module (12) receives the navigation control command processed by the MCU (5) and the positioning and orientation data parsed by the network module (3), and completes navigation control, radar data parsing and wireless two-way data communication with the ground station. The communication bus interface (1) has two independent interfaces, which respectively undertake the transmission of signal communication links and high current power supply circuits.

10. The unmanned survey vessel control circuit board based on attitude adaptive compensation according to claim 9, characterized in that, Also includes: The cooling fan (6) operates after receiving power from the first step-down module (4) to provide air cooling for the second step-down module (13) and the satellite positioning module (10); The power supply interface (11) is located on the circuit board and is used to provide external power access to the circuit board. The DC voltage of the main battery pack or external power supply is connected to the circuit board and distributed to each component after being converted by the second step-down module (13). The indicator circuit board (7) is equipped with a hull indicator socket, which is connected to the indicator module via an FPC cable. It receives the status signal sent by the MCU (5) and drives the LED indicator to indicate the status of the satellite positioning RTK fixed solution, the network differential signal, the depth sounder data analysis, the battery pack charging and discharging status, and the data storage status.

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