A positioning method, device and system for a deep-sea mining vehicle motion path

Abstract

The application discloses a positioning method, device and system for a motion path of a deep-sea mining vehicle, and relates to the technical field of seabed exploration. The method is characterized by the following steps: collecting a mining vehicle sound wave signal, a seabed sound wave signal, a water sound wave signal and an AUV sound wave signal for tracking the mining vehicle, and pre-processing the sound wave signals so as to improve the positioning accuracy of the motion path of the deep-sea mining vehicle. After the pre-processing of the sound wave signals, the sound source signal positioning is performed by using the pre-processed sound wave signals, so that the position information of the deep-sea mining vehicle is positioned. Then, the path reconstruction is performed by using the sound source positioning data, so that the motion path monitoring precision of the mining vehicle is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seabed exploration, and particularly relates to a positioning method, device and system for a motion path of a deep-sea mining vehicle. BACKGROUND

[0002] Deep-sea mining technology is an important means for developing seabed mineral resources. However, for traditional positioning methods, inertial navigation, acoustic beacon and underwater GPS system, although they can provide certain path tracking capability, their accuracy and stability are often limited under the conditions of deep-sea high pressure, strong noise interference and complex terrain. In addition, due to the complexity of the deep-sea environment, and the motion of the mining vehicle during the deep-sea mining process generates a large amount of disturbance, including sediment suspension, plume diffusion and noise propagation, which puts higher requirements on the reliability of the surrounding environment and equipment monitoring. Therefore, there is an urgent need for a positioning method for the motion path of a deep-sea mining vehicle to adapt to the complex deep-sea environment, and the motion path monitoring method of the deep-sea mining vehicle can realize high-precision motion path monitoring. SUMMARY

[0003] Therefore, the embodiments of the present application provide a positioning method, device and system for a motion path of a deep-sea mining vehicle to solve the problem of how to improve the monitoring accuracy of the motion path of the deep-sea mining vehicle in a complex deep-sea environment.

[0004] According to a first aspect, the embodiments of the present application provide a positioning method for a motion path of a deep-sea mining vehicle, comprising: acquiring a mining vehicle acoustic signal, a seabed acoustic signal, a water acoustic signal and an AUV acoustic signal for tracking the mining vehicle; preprocessing the mining vehicle acoustic signal, the seabed acoustic signal and the water acoustic signal, and outputting the preprocessed mining vehicle acoustic signal, the seabed acoustic signal and the water acoustic signal; performing acoustic source signal positioning by using the preprocessed mining vehicle acoustic signal, the seabed acoustic signal, the water acoustic signal and the AUV acoustic signal for tracking the mining vehicle, and outputting acoustic source positioning data, wherein the acoustic source positioning data comprises acoustic source intensity, acoustic source distance and three-dimensional coordinates of the acoustic source; reconstructing a motion path of the mining vehicle based on the acoustic source positioning data, and outputting the reconstructed motion path of the mining vehicle.

[0005] The positioning method for a motion path of a deep-sea mining vehicle provided by the present application pre-processes the mining vehicle acoustic signal, the seabed acoustic signal, the water acoustic signal and the AUV acoustic signal for tracking the mining vehicle, so as to improve the positioning accuracy of the motion path of the deep-sea mining vehicle. After pre-processing the acoustic signal, the acoustic source signal positioning is performed by using the pre-processed acoustic signal, the position information of the deep-sea mining vehicle is positioned, and then the path reconstruction is performed by using the acoustic source positioning data, so as to improve the motion path monitoring accuracy of the mining vehicle.

[0006] Optionally, the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal are preprocessed, including: using a band-pass filter to extract the target signal band of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal respectively.

[0007] Optionally, the sound source signal positioning is performed by using the preprocessed mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, and sound source positioning data is output, the sound source positioning data includes: sound source intensity, sound source distance and sound source three-dimensional coordinates, including: based on the target function, the sound source intensity of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal is calculated respectively, and the sound source intensity expression is:

[0008] L(r) = L0-10nlog 10 (r)

[0009] Wherein, L(r) represents the sound source intensity of any one of the obtained mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, unit: dB; L0 is the sound source intensity of the reference point of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, unit: dB; is a propagation loss factor, the value is 2-5, indicating the propagation loss of the sound wave signal in water; is the transmission distance of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, unit: m.

[0010] Based on the initial sound source intensity of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, based on the current received sound source intensity of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal and the propagation loss factor, the sound source distance of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal is calculated by using the target function.

[0011] Based on the sound source intensity, the sound source distance and the time delay data of the signal transmission of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, the sound source three-dimensional coordinate positioning of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal is performed.

[0012] Optionally, the expression for calculating the sound source distance of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal by using the target function is:

[0013]

[0014] wherein, L0 is the initial signal intensity of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal at the signal source, unit: dB; L r is the signal intensity of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal obtained, unit: dB, is the propagation loss factor.

[0015] Optionally, the expression for positioning the sound source three-dimensional coordinates of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal is:

[0016]

[0017] TE=

[0018] =

[0019]

[0020]

[0021] TE wls =

[0022] wherein, r i is the transmission distance of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, 、 、 is the sound source coordinate of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal, 、 、 is the sound source coordinate of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and AUV tracking mining vehicle sound wave signal currently received, and TE represents the error, is the signal time delay of any one of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, v is the speed of sound in water (unit: m / s), which is usually determined according to the temperature, salinity, depth and other conditions of the water, J is the Jacobian matrix, x is the current position of the estimated mining vehicle acoustic signal, seabed acoustic signal, underwater acoustic signal and acoustic signal of the AUV tracking the mining vehicle, r is the residual vector, is the weight of any one of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, is the measurement error of any one of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, TE wls minimizes the weighted error function.

[0023] Optionally, before calculating the acoustic source distance of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, time difference correction is performed.

[0024] Optionally, before reconstructing the motion path of the mining vehicle based on the acoustic source positioning data and outputting the reconstructed motion path of the mining vehicle, it includes verifying the acoustic source intensity, acoustic source distance and three-dimensional coordinates of the acoustic source.

[0025] Optionally, reconstructing the motion path of the mining vehicle based on the acoustic source positioning data includes at least one of real-time position reconstruction of the mining vehicle, motion distance reconstruction of the mining vehicle, motion process reconstruction of the mining vehicle, mining vehicle collection intensity reconstruction, and mining vehicle collection process reconstruction.

[0026] According to a second aspect, an embodiment of the present application provides a positioning device for a deep-sea mining vehicle motion path, which comprises: an acquisition module for acquiring a mining vehicle acoustic signal, a seabed acoustic signal, an underwater acoustic signal and an acoustic signal of an AUV tracking the mining vehicle; a preprocessing module for preprocessing the mining vehicle acoustic signal, the seabed acoustic signal and the underwater acoustic signal, and outputting the preprocessed mining vehicle acoustic signal, the seabed acoustic signal and the underwater acoustic signal; a processing module for performing acoustic source signal positioning using the preprocessed mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, and outputting acoustic source positioning data, the acoustic source positioning data including acoustic source intensity, acoustic source distance and three-dimensional coordinates of the acoustic source; and a reconstruction module for reconstructing the motion path of the mining vehicle based on the acoustic source positioning data, and outputting the reconstructed motion path of the mining vehicle.

[0027] The positioning device for the movement path of a deep-sea mining vehicle provided in this application acquires acoustic signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle via an acquisition module. A preprocessing module preprocesses the acoustic signals from the mining vehicle, seabed, and underwater to reduce noise or disturbances and improve the accuracy of subsequent movement path reconstruction. The preprocessed acoustic signals and the AUV tracking the mining vehicle are then sent to a processing module for positioning processing to accurately acquire sound source location data, providing data reference for obtaining an accurate movement path. Finally, a reconstruction module reconstructs the movement path of the deep-sea mining vehicle to achieve high-precision movement path monitoring.

[0028] According to a third aspect, embodiments of the present invention provide a positioning system for the movement path of a deep-sea mining vehicle, the system comprising:

[0029] The first sensor, mounted on the mining vehicle, is used to transmit noise signals;

[0030] The second sensor, located at the seabed end, is used to acquire the sound wave signal of the mining vehicle emitted from the seabed end;

[0031] The third sensor, located on the seabed, is used to acquire the seabed acoustic wave signal emitted from the seabed.

[0032] The fourth sensor, located in the water and at a preset distance from the seabed, is used to acquire underwater acoustic signals emitted from the water as noise signal output.

[0033] The fifth sensor, located on the AUV, is used to collect and output the acoustic signals of the AUV tracking the mining vehicle;

[0034] The positioning device is communicatively connected to the second, third, fourth, and fifth sensors to acquire acoustic signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, and to execute the positioning method for the deep-sea mining vehicle's movement path described above.

[0035] The positioning system for the movement path of a deep-sea mining vehicle provided in this application improves the robustness and accuracy of the system through data fusion from multiple sensors. Different sensors are deployed at different locations such as the seabed, sea surface, and water body. By utilizing acoustic time delay, signal strength, and propagation path data, multi-dimensional and three-dimensional data acquisition and analysis are conducted to reduce errors caused by incomplete or unstable data collected by a single sensor, thereby further improving the accuracy and real-time performance of movement path estimation.

[0036] According to a fourth aspect, an embodiment of the present application provides an electronic device, comprising: a memory and a processor, which are connected in communication with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the positioning method of the motion path of the deep-sea mining vehicle according to the first aspect.

[0037] According to a fifth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer instructions for causing the computer to perform the positioning method of the motion path of the deep-sea mining vehicle according to the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0038] The features and advantages of the present application will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings, which are given by way of illustration and are not intended to be limiting of the present application, in which:

[0039] Figure 1 An application scenario diagram of the positioning method of the motion path of the deep-sea mining vehicle provided by an embodiment of the present application.

[0040] Figure 2 A structure block diagram of the positioning system of the motion path of the deep-sea mining vehicle provided by an embodiment of the present application.

[0041] Figure 3 A flowchart of the positioning method of the motion path of the deep-sea mining vehicle provided by an embodiment of the present application.

[0042] Figure 4 A structure block diagram of the positioning device of the motion path of the deep-sea mining vehicle provided by an embodiment of the present application.

[0043] Figure 5 A structure block diagram of the electronic device provided by an embodiment of the present application.

[0044] REFERENCE NUMERALS

[0045] 100-first sensor; 200-second sensor; 300-third sensor; 400-fourth sensor; 500-fifth sensor; 600-positioning device; 1-acquisition module; 2-preprocessing module; 3-processing module; 4-reconstruction module; 51-processor; 52-memory. DETAILED DESCRIPTION

[0046] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0047] It should be noted that the positioning method, device and system of the motion path of the deep-sea mining vehicle provided in the present application, by installing a first sensor on the mining vehicle, the noise signal emitted by the mining vehicle during operation is monitored in real time by using the distributed underwater sensors (second sensor to fifth sensor) arranged underwater, and the signal processing and positioning method provided in the present application is combined to realize accurate path tracking of the deep-sea mining vehicle.

[0048] As shown in Figure 1 , it is a schematic diagram of the application scene of the positioning method of the motion path of the deep-sea mining vehicle provided in the embodiments of the present application. The application scene includes: the deep-sea mining vehicle arranged on the seabed, the offshore operation platform for recovering positioning data and displaying and outputting the reconstructed motion path of the mining vehicle, and the positioning system of the motion path of the deep-sea mining vehicle. In its application scene, the deep-sea mining vehicle on the seabed emits a noise signal, the positioning system of the motion path of the deep-sea mining vehicle collects and processes the noise signal emitted by the deep-sea mining vehicle on the seabed to generate sound source positioning data, and then reconstructs the motion path of the deep-sea mining vehicle using the sound source positioning data, and transmits the reconstructed motion path of the deep-sea mining vehicle and the positioning information to the offshore operation platform for display, so as to control the operation of the deep-sea mining vehicle by the offshore operation personnel, and ensure the safety and accuracy of underwater operation.

[0049] Among them, the positioning system of the motion path of the deep-sea mining vehicle can include: a plurality of sensors arranged on the deep-sea mining vehicle, different underwater positions and AUV (Autonomous Underwater Vehicle, autonomous underwater vehicle).

[0050] As shown in Figure 2 , it is a schematic diagram of the structure block diagram of the positioning system of the motion path of the deep-sea mining vehicle provided in the embodiments of the present application. The positioning system of the motion path of the deep-sea mining vehicle provided in the embodiments of the present application includes: a first sensor 100, a second sensor 200, a third sensor 300, a fourth sensor 400, a fifth sensor 500 and a positioning device 600.

[0051] The first sensor 100 is arranged on the mining vehicle and is used to send a noise signal. The second sensor 200 is arranged at the sea bottom end and is used to obtain a noise signal output from the sea bottom end to emit a vehicle sound wave signal. The third sensor 300 is arranged at the sea bed surface and is used to obtain a noise signal output from the sea bed to emit a sea bed sound wave signal. The fourth sensor 400 is arranged in the water body and is kept at a preset distance from the sea bottom end. The fourth sensor 400 is used to obtain a noise signal output from the water to emit a water sound wave signal. The fifth sensor 500 is arranged on the AUV and is used to collect and output a sound wave signal of the AUV tracking the mining vehicle.

[0052] The positioning device 600 is in communication connection with the second sensor 200, the third sensor 300, the fourth sensor 400, and the fifth sensor 500. The positioning device 600 is used to obtain the vehicle sound wave signal, the sea bed sound wave signal, the water sound wave signal, and the sound wave signal of the AUV tracking the mining vehicle, and execute a corresponding positioning method of the motion path of the deep-sea mining vehicle.

[0053] In some embodiments, the deep-sea mining vehicle emits a noise signal by carrying the first sensor 100 (an underwater noise sensor). A multi-level sea bottom noise monitoring system is constituted by combining the second sensor 200, the third sensor 300, the fourth sensor 400 (fixed monitoring sensors), and the fifth sensor 500 and the positioning device 600 arranged at different positions, so as to realize accurate positioning and tracking of the motion path of the mining vehicle.

[0054] In some embodiments, the first sensor 100 is arranged in multiple numbers. The first sensor 100 (such as an underwater sensor) can be arranged around the mining vehicle in a quadrilateral or hexagonal arrangement.

[0055] Preferably, the multiple first sensors 100 are arranged in a split-column arrangement near the mining vehicle. The interval distance between the first sensor 100 and the mining vehicle can be analyzed according to specific conditions, which is not limited herein.

[0056] In some embodiments, the arranged sensors can be divided into three parts: the first sensor 100 carried by the mining vehicle. Specifically, the first sensor 100 is carried at the tail of the mining vehicle to send a noise signal. The mining vehicle as an active noise source emits a noise signal through the first sensor 100, which makes the noise signal can provide the main basis for tracking the path of the mining vehicle.

[0057] Optionally, the first sensor 100 is a noise sensor, which is located at the tail of the mining vehicle and can emit noise signals of specific frequency and intensity, which can propagate in the water body and be received by other sensors (second sensor 200, third sensor 300, fourth sensor 400, fifth sensor 500). The arrival time, intensity attenuation, frequency spectrum change and other information data of the noise signals emitted by the first sensor 100 are measured or collected by other sensors (second sensor 200, third sensor 300, fourth sensor 400, fifth sensor 500), and then the position and movement path of the mining vehicle are inferred according to the collected information data, so as to realize the positioning of the movement path of the deep-sea mining vehicle.

[0058] Optionally, the first sensor 100 arranged on the mining vehicle is used as a noise source, which is responsible for emitting underwater acoustic signals. The first sensor 100 periodically or continuously emits acoustic signals of specific frequency and intensity at the tail of the mining vehicle. These signals will propagate in the form of sound waves in the water. It should be noted that the first sensor 100 itself does not receive signals, but uses the propagation characteristics (such as attenuation and frequency shift) of sound waves in combination with the receiving results of other sensors to locate the position of the mining vehicle.

[0059] Optionally, during data collection, the first sensor 100 of the mining vehicle emits periodic noise pulses, and the time interval, frequency and amplitude of each pulse are set by the user, thereby providing a reference for subsequent signal analysis and positioning.

[0060] In some embodiments, the second sensor 200, the third sensor 300 and the fourth sensor 400 are fixed monitoring sensors. The second sensor 200 is a seabed end sensor, the third sensor 300 is a sea floor sensor, and the fourth sensor 400 is a water body sensor.

[0061] The seabed end sensor is arranged about 50 meters away from the seabed and is equipped with a base and a floating ball. The seabed end sensor also includes an acoustic sensor, which is used to monitor acoustic signals from the seabed, i.e. sound waves from the mining vehicle. Since the noise signals will attenuate and change in frequency spectrum when propagating in the water, the position of the mining vehicle can be inferred by detecting noise characteristics (such as arrival time, frequency, amplitude change and other information data) through the second sensor 200. The sound from the mining vehicle can be monitored in real time, and preliminary data can be provided for subsequent path calculation.

[0062] The sea floor sensor is directly placed on the sea floor and closely adheres to the seabed sediments. It can monitor acoustic signals from the sea floor, especially data information about the interaction between seabed sediments and noise signals when the mining vehicle passes. The third sensor 300 can detect the seabed disturbance caused by the mining vehicle activity, i.e. sea floor sound waves, to further provide reliable support for positioning and record the physical state of the sea floor and the disturbance signals during the movement of the mining vehicle.

[0063] The water body sensor is located about 500 meters from the seabed and mainly in the water body. It monitors the acoustic signals propagating in the water body, can receive noise signals from the seabed, and analyzes the propagation characteristics in the water body, i.e. the acoustic signals in the water. Because the acoustic wave propagates far in the water body and decays slowly, the water body sensor can receive remote noise signals from the mining vehicle, especially for deep water areas or when the mining vehicle is in a deeper water layer.

[0064] The fifth sensor 500 carried by the AUV is mainly used for real-time tracking of the movement path of the mining vehicle. The AUV can navigate in the water, cooperate with other sensors, and continuously receive and record noise signals emitted by the mining vehicle in the entire monitoring area. The fifth sensor 500 receives noise signals from the mining vehicle and combines the navigation track of the AUV to accurately determine the movement track of the mining vehicle, i.e. the AUV tracks the acoustic signals of the mining vehicle. The fifth sensor 500 can accurately locate the current position of the mining vehicle through time difference, frequency spectrum analysis, etc. of the noise signals of the mining vehicle.

[0065] In some embodiments, the second sensor 200 is located in seawater about 50 meters from the seabed, and is installed in combination with a weighted base and a floating ball. The main function of the second sensor 200 is to receive noise signals emitted from the mining vehicle. The second sensor 200 captures acoustic waves propagating in the water through an underwater microphone (or hydrophone). The second sensor 200 records the intensity, frequency change and arrival time of the signal. By analyzing the time delay and frequency spectrum of the signal, the second sensor 200 can estimate the relative position of the noise source. During data collection, the second sensor 200 periodically samples the acoustic signals in the water to obtain real-time data of the noise signals of the mining vehicle.

[0066] The third sensor 300 is located on the seabed surface and directly contacts the seabed sediments. It is specially used to monitor low-frequency noise and vibration caused by the mining vehicle. The third sensor 300 uses a vibration sensor or a hydrophone to record acoustic signals from the seabed. These acoustic signals are usually low-frequency acoustic waves generated by the disturbance of the seabed sediments caused by the movement of the mining vehicle. The third sensor 300 can capture the disturbance and vibration generated by the movement of the mining vehicle on the seabed by sensing acoustic waves. For example, the third sensor 300 records the amplitude, frequency, duration, etc. of the signal each time the mining vehicle moves, which further helps to locate the mining vehicle.

[0067] The fourth sensor 400 is located in the water body 500 meters away from the seabed, and is mainly responsible for receiving the sound wave signals propagating in the water. The fourth sensor 400 can listen to the remote noise source and record the intensity, frequency and arrival time of the signal. In the data acquisition process, the fourth sensor 400 receives the noise signal from the seabed. The noise signal will attenuate during propagation, especially at a long distance, and the signal intensity will be significantly weakened. The role of the fourth sensor 400 is to capture these long-range signals and calculate the relative position of the mining vehicle by combining the physical model of sound wave propagation. The fourth sensor 400 samples the signal at a certain time interval and transmits the received signal to the positioning device 600. The physical model of sound wave propagation can refer to the actual model of the prior art, which will not be described here.

[0068] The fifth sensor 500 is mainly responsible for tracking the real-time motion path of the mining vehicle. The fifth sensor 500 obtains the positioning information of the mining vehicle by receiving acoustic signals (such as noise signals emitted by the first sensor 100) from the mining vehicle. In the data acquisition process, the AUV travels along the path of the mining vehicle, and the fifth sensor 500 captures the constantly changing noise signal. The fifth sensor 500 can record the time delay, frequency, intensity and other parameters of the noise signal. By analyzing these data, the positioning device 600 can estimate the position of the mining vehicle in real time.

[0069] In some embodiments, the first sensor 100 is mainly responsible for emitting noise signals, and the signal intensity at the emission point is generally a known reference value. The second sensor 200 is a seabed sensor, and the second sensor 200 is located at a depth of 50 meters. The intensity of the noise signal emitted by the first sensor 100 will attenuate as the distance between the mining vehicle and the sensor increases. Therefore, the setting of the second sensor 200 directly affects the accuracy of the signal, and the sensitivity of the effective signal range of the second sensor 200 to low-frequency noise. Low-frequency signals usually propagate far, but will be greatly attenuated during transmission.

[0070] The third sensor 300 is directly installed on the seabed surface and monitors the low-frequency or ultra-low-frequency signal caused by the disturbance of the mining vehicle to the sediment. Due to the good conduction effect of the sediment near the seabed, the attenuation of the low-frequency signal is small, but its propagation path will still be affected by factors such as water depth and sediment type. The third sensor 300 mainly detects low-frequency noise, and the frequency characteristics also have a great influence on the signal intensity.

[0071] The fourth sensor 400 is located 500 meters above the seabed. The signal strength received by the fourth sensor 400 is affected by the attenuation of the water. The fifth sensor 500 is mounted on the AUV and is mainly used to track the real-time movement path of the mining vehicle. The fifth sensor 500 is usually located near the mining vehicle, and its signal strength is affected by the relative position between the AUV and the mining vehicle.

[0072] Optionally, the fifth sensor 500 can work in conjunction with the AUV and combine the AUV's position information and acoustic signal analysis to further improve the accuracy of mining vehicle path reconstruction. The fifth sensor 500 periodically collects noise signals and transmits the data to the positioning device 600 in real time to achieve positioning analysis of the execution path.

[0073] It should be noted that the coverage radius of the sensors set in this application covers the entire mining activity area to ensure the reception of mining vehicle noise signals. Furthermore, the frequency identification range of the second sensor 200, the third sensor 300, the fourth sensor 400, and the fifth sensor 500 is the frequency range capable of effectively capturing mining vehicle noise, and their transmit and receive signal power is greater than their transmit noise power.

[0074] The positioning device 600 is used to receive the mining vehicle acoustic signals, seabed acoustic signals, underwater acoustic signals and AUV tracking the mining vehicle sent by the second sensor 200, the third sensor 300, the fourth sensor 400 and the fifth sensor 500, and to implement a positioning method for the movement path of the deep-sea mining vehicle using these signals.

[0075] Optionally, the positioning device 600 may also include a communication module or unit for transmitting data with the offshore operating platform, thereby transmitting sound source positioning data and the reconstructed movement path of the deep-sea mining vehicle.

[0076] Specifically, such as Figure 3 The diagram shown is a flowchart illustrating the method for locating the movement path of a deep-sea mining vehicle according to an embodiment of this application. This method can be applied to the positioning device 600, or it can be installed in a device or processing unit. The specific implementation steps include:

[0077] S1 acquires the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle.

[0078] In this embodiment, the acoustic signals of the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle can be acquired from the second sensor 200, the third sensor 300, the fourth sensor 400, and the fifth sensor 500.

[0079] S2 preprocesses the acoustic signals from the mining vehicle, seabed, and underwater, and outputs the preprocessed acoustic signals from the mining vehicle, seabed, and underwater.

[0080] In this embodiment, preprocessing the acoustic signals from the mining vehicle, the seabed, and the underwater can involve performing signal band analysis, signal separation, and signal band extraction on the acoustic signals from the mining vehicle, the seabed, and the underwater.

[0081] In some embodiments, signal band analysis of mining vehicle acoustic signals, seabed acoustic signals, and underwater acoustic signals can be performed as follows:

[0082] The acoustic signal of the mining vehicle is mainly low-frequency to mid-frequency signal. In band analysis, low-frequency signals often have strong propagation capabilities, so they can be used to estimate the distance between the mining vehicle and the second sensor 200. By analyzing the spectrum, the low-frequency components of the signal are extracted, which helps to identify the activity of the mining vehicle. The received noise signal is processed by a high-pass filter to remove low-frequency background noise and other natural interference in the water.

[0083] Seabed acoustic signals are low-frequency noise generated by mining vehicles disturbing seabed sediments. These signals are usually located in a very low frequency band (1 Hz-100 Hz). Band analysis of seabed acoustic signals can separate the vibration frequencies associated with mining vehicle operations, thereby analyzing the specific location and operating status of the mining vehicles.

[0084] Underwater acoustic signals originate from the seabed. Band analysis of these signals helps identify the variations in frequency across different propagating frequencies. Since water attenuates high-frequency signals more significantly, band analysis can extract high-frequency and mid-frequency signals (above 500 Hz), aiding in the study of water propagation effects and helping to locate the path of mining vehicles. Furthermore, band analysis can effectively distinguish between noise generated by mining vehicle activity and natural background noise such as water flow.

[0085] AUVs track the acoustic signals of mining vehicles. During the band analysis process, the location of the mining vehicle can be inferred by receiving noise signals of different frequency bands. Furthermore, the positioning accuracy can be further improved by analyzing the propagation time delay and amplitude changes of signals of different frequency bands.

[0086] Optionally, the AUV receives signals in a wide frequency range, including low-frequency (10 Hz-500 Hz) and mid-frequency (500 Hz-1000 Hz) signals. Band analysis of the received acoustic signals can help extract key information from the acoustic signals for accurate positioning.

[0087] In some embodiments, signal separation of the mining vehicle acoustic signal, seabed acoustic signal, and underwater acoustic signal can be performed as follows:

[0088] The acoustic signal of the mining vehicle mainly includes the noise generated by the mining vehicle and the background noise. The signal separation process can be as follows: First, the noise of the mining vehicle is separated from the low-frequency to mid-frequency signals by filtering the frequency range. Then, the acoustic signal of the mining vehicle is extracted by using waveform characteristics and time delay information through time-frequency separation methods (such as wavelet transform).

[0089] Seabed acoustic signals are low-frequency signals generated by the disturbance of mining vehicles. Signal separation can be achieved by using a low-pass filter to remove high-frequency noise and by using a separation algorithm with a specific frequency range (such as a band-pass filter) to extract the bottom disturbance signal associated with the mining vehicle.

[0090] The sources of underwater acoustic signals are quite complex, including low-frequency signals from the seabed and background noise from the water body. When separating underwater acoustic signals, high-frequency noise can be filtered out to remove water flow or other environmental noise. Combined with the known noise characteristics of the mining vehicle, the acoustic signal of the mining vehicle can be effectively separated.

[0091] In some embodiments, when the fifth sensor 500 collaborates with other sensors to receive noise signals from the mining vehicle, the movement path of the AUV and the time delay of the noise signals can provide clues for signal separation. Then, through waveform matching and time delay analysis, the signals received by the AUV can be compared with the data of other sensors to separate the specific acoustic signals of the mining vehicle, thereby removing background noise and other underwater signals.

[0092] Optionally, since the signal emitted by the first sensor 100 is known periodic or pulse noise, the noise source of the mining vehicle can be effectively separated from the signals collected by other sensors by using signal separation technology and comparing it with a known transmitted signal template.

[0093] In some embodiments, the acoustic signals of the mining vehicle, the seabed, and the underwater can be preprocessed, and the target signal bands can be extracted from the acoustic signals of the mining vehicle, the seabed, and the underwater using bandpass filters.

[0094] In this embodiment, the first sensor 100 mounted on the mining vehicle is responsible for emitting periodic or pulsed noise signals. These signals propagate in the water and are received by other sensors. In the data processing stage, the signals emitted by the mining vehicle are first transformed from the time domain to the frequency domain by performing a Fourier transform to obtain the spectrum of the signal. Then, based on this, the target signal band is extracted to identify the noise characteristics in different frequency bands.

[0095] Furthermore, since the noise signals from mining vehicles typically have strong low-frequency components, signals in the low-frequency band (e.g., 0–1000 Hz) can be extracted by designing a low-pass filter. These low-frequency signals are usually generated by mechanical operations, engine sounds, etc., and have strong propagation capabilities, enabling them to travel long distances in water.

[0096] The second sensor 200, the third sensor 300, and the fourth sensor 400 are mainly responsible for receiving noise signals from the seabed and water bodies. They are located at different depths and positions and collect noise information from different sources.

[0097] To extract the target signal band from the acoustic signal of the mining vehicle, it is necessary to perform a Fourier transform on the acoustic signal received by the second sensor 200 to convert the acoustic signal into frequency domain data. The second sensor 200 mainly receives low-frequency noise signals emitted by the mining vehicle, such as low-frequency sounds caused by machine vibration, thrusters, etc. In order to extract these low-frequency signals, a low-pass filter can be used to set the frequency range between 0 and 500 Hz.

[0098] The target signal band is obtained by extracting the waveband of the seabed acoustic signal. Since the vibration generated by the operation of mining vehicles is usually low-frequency or ultra-low-frequency signal, the target signal band of the seabed acoustic signal is mainly concentrated in the low-frequency band, and the range of 0–1000 Hz can usually be selected for extraction.

[0099] The target signal band is obtained by extracting the waveband of the acoustic signal in water. Due to the noise propagation characteristics in water, high-frequency signals attenuate relatively quickly, while low-frequency signals can propagate further. Therefore, the target signal band extracted from the acoustic signal in water usually covers the low-frequency and mid-frequency range (e.g., 100 Hz to 2000 Hz).

[0100] Specifically, signal band extraction from the acoustic signals of mining vehicles, seabed, and underwater can be performed as follows:

[0101] First, the raw signal data, namely the sound wave signal from the mining vehicle, the sound wave signal from the seabed, and the sound wave signal from the water, are processed, and the target frequency band signal is extracted using a bandpass filter:

[0102] H(f) =

[0103] Secondly, the filtered signal is used:

[0104] S-filter(t) = F-1

[0105] Then, wavelet transform is used to separate noise from signal:

[0106] =

[0107] Where H(f) is the filter, F is the Fourier transform, Soriginal(t) is the original signal, and Sfiltered(t) is the filtered signal. Here are the wavelet transform coefficients, and λ is the noise threshold. For frequency.

[0108] S3 uses the pre-processed acoustic signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle to locate the sound source and outputs sound source location data, which includes: sound source intensity, sound source distance, and three-dimensional coordinates of the sound source.

[0109] In some embodiments, after acquiring the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, a joint calculation can be performed using an objective function to obtain the sound source intensities of these signals. Alternatively, the sound source intensity can be understood as representing the acoustic intensity localization of each sensor and the movement of the mining vehicle. The expression for the sound source intensity can be:

[0110] L(r) = L0 - 10nlog 10 (r)

[0111] L(r) is the sound source intensity received at a distance r, which is the sound source intensity of any one of the acquired sound wave signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, in dB. L0 is the sound source intensity at a reference point (e.g., near the first sensor), which is the sound source intensity at the reference point of any one of the acquired sound wave signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, in dB. The propagation loss factor, usually with a value of 2-5, represents the propagation loss of sound waves in water, and also depends on environmental factors such as water temperature, salinity, and depth. The distance between the sensor and the noise source (mining vehicle) is the transmission distance of any one of the following sound wave signals: the sound wave signal from the mining vehicle, the sound wave signal from the seabed, the sound wave signal from the water, and the sound wave signal from the AUV tracking the mining vehicle. The unit is meters.

[0112] In some embodiments, L(r) is the signal strength of the acoustic signal received by the second / third / fourth / fifth sensor from the noise source emitted by the first sensor, and L0 is the signal strength received at a user-preset or known location.

[0113] In this embodiment, the distance to the output sound source can be:

[0114] Based on the initial sound source intensities of the sound wave signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, and based on the currently received sound source intensities and propagation loss factors of the sound wave signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, the sound source distances of the sound wave signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle are calculated using an objective function.

[0115] Specifically, the expression for the distance to the sound source is:

[0116]

[0117] Where L0 is the initial signal intensity at the signal source of any one of the following sound wave signals: the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the sound wave signal from the AUV tracking the mining vehicle, in dB. r The signal intensity of any one of the acoustic signals acquired, including the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, is expressed in dB. This is the propagation loss factor.

[0118] In this embodiment, the values ​​of L0 and 𝑛 can be adjusted to adapt to different measurement conditions and environments, thereby enabling a more accurate determination of the sound source location when calculating the sound source distance and intensity.

[0119] In some embodiments, the signal source can be determined by the user, for example: a first sensor mounted on the mining vehicle is determined as the signal source, i.e., the initial signal strength is the acoustic signal strength of the noise signal emitted by the first sensor; L r It can be an acoustic signal collected by a second / third / fourth / fifth sensor.

[0120] Optionally, time difference correction is performed before calculating the source distances of the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, thereby improving positioning accuracy and system robustness.

[0121] Because the propagation of underwater signals is affected by factors such as water salinity, temperature, depth, ocean currents, and seabed sediment, the calculation of signal distance needs further correction.

[0122] First, time difference correction is performed on the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle. The expression is as follows:

[0123]

[0124] in, The location of noise signals, such as the location of an underwater mining vehicle; The time difference between the received signals of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal, and the AUV tracking the mining vehicle, i.e., the time difference between the received acoustic signals of the second to the fifth sensors; To receive the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, the location is any two of the locations between the second and fifth sensors. The speed of sound in water is determined by the user or obtained from actual measurement data.

[0125] In this embodiment, minimizing the time difference to obtain the multipath transmission distance helps improve the positioning accuracy in subsequent steps.

[0126] Optionally, a sound speed correction is performed, whereby the sound speed c is corrected for variations in depth Z, temperature T, and salinity S as follows:

[0127] c(z,T,s)=c0+α T T+α s S-βz

[0128] Where c(z,T,s) is the corrected speed of sound in water, in meters per second, c0 is the reference speed of sound in water, in meters per second, and α T This is a temperature correction factor, where T is the water temperature in degrees Celsius, and α is the temperature correction factor. s Here, S is the salinity correction factor, β is the depth correction factor, and z is the water depth, in meters. For details on the temperature correction factor, depth correction factor, and salinity correction factor, please refer to the existing data, which will not be elaborated here.

[0129] In some embodiments, the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle are used, and the time difference between the different signals is used to determine the location information. The expression can be:

[0130] R=v×Δt

[0131] in: Δt represents the speed of sound in water, in meters per second; Δt represents the propagation delay of any one of the following sound wave signals: the mining vehicle's sound wave signal, the seabed's sound wave signal, the underwater sound wave signal, and the sound wave signal from the AUV tracking the mining vehicle, in seconds.

[0132] In this embodiment, determining the three-dimensional coordinate location of the sound source can be done as follows:

[0133] Based on the sound source intensity, sound source distance, and signal transmission delay data of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal, and AUV tracking the mining vehicle sound wave signal, the three-dimensional coordinate positioning of the sound source of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal, and AUV tracking the mining vehicle sound wave signal is performed.

[0134] Specifically, the location is achieved by acquiring the signal strength, time delay data, and propagation model of the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle. Specifically, this can involve acquiring multiple coordinates and corresponding signal delays Δt from the first sensor 100 to the fifth sensor 500, and describing the distance between each sensor and the mining vehicle using the following method:

[0135]

[0136] TE=

[0137] =

[0138]

[0139]

[0140] TE wls =

[0141] Where, r i The transmission distance of any one of the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle is defined as the distance from which the signal is transmitted. , , To determine the source coordinates of any sound wave signal from among the sound wave signals emitted by the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, , , Let TE represent the source coordinates of any acoustic signal among the currently received acoustic signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle, and let TE represent the error. Let be the signal delay of any one of the following acoustic signals: the mining vehicle's acoustic signal, the seabed's acoustic signal, the underwater acoustic signal, and the acoustic signal from the AUV tracking the mining vehicle. Let be the speed of sound in water (in meters per second), usually determined based on water temperature, salinity, depth, etc. Let J be the Jacobian matrix, x be the estimated current position of any one of the following acoustic signals: the mining vehicle's acoustic signal, the seabed's acoustic signal, the underwater acoustic signal, and the acoustic signal from the AUV tracking the mining vehicle, and r be the stagger vector. It is the weight of any one of the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle. It is the measurement error of any one of the acoustic signals from the mining vehicle, the seabed, the underwater, and the AUV tracking the mining vehicle, TE wls Minimize the weighted error function.

[0142] In this embodiment, by calculating the distance from each sensor to the target, the target's position in three-dimensional space can be accurately determined; the error function (TE) and the weighted error function (TE) are calculated. wls This helps minimize errors during the positioning process and improve positioning accuracy; iterative calculations can gradually optimize the estimation of the target position until convergence is achieved; and by considering the measurement error of each sensor, the positioning accuracy can be improved. 𝑖 The weighted least squares method can improve the system's robustness to outliers.

[0143] S4, reconstruct the motion path of the mining vehicle based on the sound source localization data, and output the reconstructed motion path of the mining vehicle.

[0144] In this embodiment, the movement path of the mining vehicle is reconstructed based on the sound source localization data, including at least one of the following: real-time position reconstruction of the mining vehicle, movement distance reconstruction of the mining vehicle, movement process reconstruction of the mining vehicle, acquisition intensity reconstruction of the mining vehicle, and acquisition process reconstruction of the mining vehicle.

[0145] Among them, the real-time position reconstruction of the mining truck can be achieved by using sound source localization data (delay, signal strength): that is, based on the delay and intensity of the sound wave signals received by different sensors, the distance and position between the sensors and the mining truck can be calculated.

[0146] Using existing motion state models, path estimation is performed based on the motion characteristics of the mining vehicle (such as speed, acceleration, turning, etc.). Real-time position and trajectory estimation can be based on sound source localization data (such as: positioning data, acoustic distance measurement results, motion state estimation and environmental impact correction). The motion trajectory of the mining vehicle is reconstructed in real time. The path reconstruction process mainly includes several steps such as position estimation, path smoothing and motion state analysis. These can be found in existing technologies and will not be elaborated here.

[0147] In this application, the signal propagation delay from the mining vehicle to each fixed sensor is calculated using sound source localization data to estimate the actual distance. By utilizing the collaboration of multiple sensors and sound source localization data, the position of the mining vehicle can be estimated in real time.

[0148] Assuming we use five sensors for positioning, we first need to calculate the distance based on the time delay data between the sensors and the mining vehicle. Reconstructing the mining vehicle's movement distance can be done through path reconstruction. This requires not only calculating the mining vehicle's instantaneous position using the sensors but also inferring its trajectory based on a kinematic model. The mining vehicle's motion state (such as speed and acceleration) can be obtained through accelerometers, gyroscopes, or other sensors, or it can be inferred from changes in position.

[0149] The reconstruction of the mining truck's movement can be hampered by noise from the seabed environment and sensor errors, often resulting in jerky or uneven paths. Therefore, smoothing the mining truck's trajectory is necessary. By continuously estimating the mining truck's position, its complete trajectory can be reconstructed. The path reconstruction process can be divided into several stages, such as the start-up stage, the stabilization stage, and the turning stage. Based on the trajectory reconstruction results, the mining truck's movement process can be analyzed.

[0150] The intensity reconstruction of the mining truck's data acquisition can be based on the positive correlation between the mining truck's operating intensity and the intensity of the received acoustic signal. During the acquisition process, the sound waves generated by the noise source are affected by factors such as distance, propagation medium, and seabed sediments when they propagate through the water to the sensor. Therefore, there is a certain functional relationship between the acoustic signal intensity and the acquisition intensity, which can be reconstructed.

[0151] Mining truck data acquisition process reconstruction can infer the mining truck's activities during the acquisition process based on the real-time signal strength. By analyzing the signal attenuation pattern, it can be inferred whether the mining truck is in an area with a thick ore layer or whether the mining truck has come into contact with the target mineral.

[0152] A specific implementation scenario could be as follows: During the deployment of sensors for reconstructing the movement path of a deep-sea mining vehicle, a detailed survey and analysis of the work area is first conducted to select a suitable water depth, seabed structure, and signal propagation environment. An acoustic propagation model is then used to simulate signal transmission and sensor response. Based on this, a first sensor 100 is installed at the rear of the mining vehicle to ensure it can transmit acoustic signals to surrounding sensors in real time. Then, a second sensor 200 is deployed on the seabed, with a counterweight base and buoys ensuring its stability, receiving signals from the mining vehicle at intervals of approximately 50 meters. A third sensor 300 is placed on the seabed surface to capture acoustic signals from the mining vehicle and its surrounding environment. A fourth water sensor is installed in the water layer 500 meters above the seabed to monitor acoustic signals propagating in the water. Finally, a fifth sensor 500 is mounted on an AUV, moving synchronously with the mining vehicle to track its movement path in real time and collect relevant data. After deployment, data calibration and testing are performed to ensure the coordinated operation of each sensor. Noise data is collected in real time when the mining vehicle starts working. The movement path of the mining vehicle is located and reconstructed through time delay and intensity analysis to ensure accurate monitoring and safe and efficient operation of the entire process.

[0153] The method for locating the movement path of a deep-sea mining vehicle provided in this application includes, before reconstructing the movement path of the mining vehicle based on sound source localization data and outputting the reconstructed movement path of the mining vehicle, verifying the sound source intensity, sound source distance, and three-dimensional coordinates of the sound source.

[0154] Specifically, the process requires initial data preprocessing to align the time series and generate equally spaced time series coordinates. State estimation and smoothing filtering are then performed based on these time coordinates, followed by Bezier smoothing to obtain a continuous trajectory. Trajectory processing considering kinematic errors yields an estimated mining vehicle path. The distribution characteristics of errors in three-dimensional space are analyzed; positioning accuracy is typically higher in areas with dense sensor density. Error changes over time are observed, and the adaptability of the dynamic model is analyzed. Noise-based positioning errors are reduced by improving signal processing algorithms (such as adaptive filtering). A sound velocity distribution model is used to minimize the impact of sound velocity errors on the positioning results.

[0155] Then, the sound source intensity was mutually verified:

[0156] The signal strength calculation formula and acoustic propagation model were verified by testing the signal strength received by different sensors. The signal strength calculation formula is expressed as follows:

[0157]

[0158] in, For the time difference, The received sound pressure level (in dB). For reference sound pressure level, the unit is Pascal (Pa), usually taken as... =20×10 −6 Pa (a commonly used value in water), where A is the receiving area for sound wave propagation, which usually depends on the sensor's receiving mode (such as single-point reception or array reception).

[0159] In this embodiment, using a known sound pressure level and reference sound pressure To calculate the time difference of sound wave propagation This allows for precise verification of the accuracy of acoustic models and measuring equipment.

[0160] Since the first sensor 100 is a noise source, the verification of acoustic intensity mainly relies on the power and propagation characteristics of the noise signal emitted by the mining vehicle. The second sensor 200 is located 50 meters below the seabed, and the noise signal it receives undergoes a certain degree of attenuation. The third sensor 300 is located on the seabed surface and mainly monitors low-frequency signals propagating in sediments. For the acoustic intensity verification of the third sensor 300, it is first necessary to confirm the signal strength it receives, and then obtain the corresponding acoustic intensity. Low-frequency signals usually propagate over long distances and attenuate slowly; therefore, the verification results of the third sensor 300 should show its high receiving capability. The fourth sensor 400 is located at a deeper level in the water, and the signal it receives usually travels a long propagation path and is significantly attenuated. Since high-frequency signals are strongly attenuated in water, the acoustic intensity verification of the fourth sensor needs to consider the signal attenuation effect. The fifth sensor 500 is responsible for tracking the movement path of the mining vehicle, and the received signal intensity mainly comes from the noise signal of the mining vehicle. Since the fifth sensor 500 is close to the mining vehicle, the received signal is usually strong. Therefore, when performing acoustic intensity verification, the verification result should show a high signal strength. When calculating the actual propagating acoustic intensity, if the received signal strength is close to the theoretical value, it indicates that the signal propagation effect is good and the acoustic intensity verification is passed.

[0161] Acoustic distance mutual verification:

[0162] In a multi-sensor positioning system, each sensor can independently calculate its distance *r* from a noise source (such as a deep-sea mining vehicle) by analyzing the relationship between time delay and the speed of sound. The core of acoustic distance cross-verification lies in the fact that when multiple sensors receive signals from the same noise source, the distances calculated by each sensor may differ due to variations in propagation paths, propagation losses, and time delays. By comparing these distances and combining them with methods such as position calibration and propagation model correction, positioning accuracy can be effectively improved and system errors corrected.

[0163] The acoustic distance mutual verification formula is expressed as follows:

[0164]

[0165] in, The average distance, For the first The distance calculated by each sensor, such as the signal transmission distance of the mining vehicle's acoustic signals, seabed acoustic signals, underwater acoustic signals, and the acoustic signals of the AUV tracking the mining vehicle, acquired by the second to fifth sensors. For the first The weights of individual sensors, such as the weights of the second through fifth sensors, are typically determined based on the sensor's accuracy and signal strength.

[0166] In this embodiment, by assigning weights to each sensor, the contribution of each sensor to the total distance estimation can be more accurately reflected. The weights can be based on the sensor's accuracy, reliability, or signal strength. Using a weighted average, the positioning of multiple sensors can be made more accurate and reliable.

[0167] Acoustic localization mutual verification:

[0168] Acquire acoustic signals from mining vehicles, seabed, underwater, and AUV-tracked mining vehicles; calculate the distance between each signal and the noise signal emitted by the mining vehicle; and perform corrections based on time differences, such as mutual verification between various signals or data and verification based on minimum time difference.

[0169] The positioning method for the movement path of a deep-sea mining vehicle provided in this application utilizes a multi-sensor system to monitor and locate the mining vehicle and its operating environment in real time. This system consists of five main sensors: a first sensor 100 at the rear of the mining vehicle, a second sensor 200 at the seabed, a third sensor 300 on the seabed, a fourth sensor 400 in the water, and a fifth sensor 500 mounted on an AUV, forming a multi-layered, multi-dimensional acoustic monitoring network. Its advantage lies in overcoming the limitations of traditional deep-sea positioning technologies through multi-sensor data fusion and acoustic time delay analysis, achieving real-time, high-precision movement path reconstruction. This positioning method not only improves the positioning accuracy and safety in deep-sea mining operations but also provides a novel solution for dynamic monitoring in complex seabed environments.

[0170] The positioning method for the movement path of a deep-sea mining vehicle provided in this application uses the mechanical noise of the mining vehicle as an active source, the noise of seabed sediment disturbance as a passive source, the water propagation noise as a long-range attenuation signal, and the AUV tracking signal as a dynamic reference signal, and uses them together for positioning to improve high-precision positioning and anti-interference capability in complex environments.

[0171] Furthermore, it should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0172] Accordingly, please refer to Figure 4 This invention provides a positioning device for the movement path of a deep-sea mining vehicle, comprising:

[0173] Acquisition module 1 is used to acquire acoustic signals from mining vehicles, seabed, underwater, and AUV tracking mining vehicles. For details, please refer to step S1.

[0174] Preprocessing module 2 is used to preprocess the acoustic signals of the mining vehicle, the seabed, and the underwater, and output the preprocessed acoustic signals of the mining vehicle, the seabed, and the underwater. For details, please refer to step S2.

[0175] Processing module 3 is used to locate the sound source signal using the preprocessed sound wave signal from the mining vehicle, the sound wave signal from the seabed, the sound wave signal from the water, and the sound wave signal from the AUV tracking the mining vehicle, and output the sound source location data. The sound source location data includes: sound source intensity, sound source distance, and three-dimensional coordinates of the sound source. For details, please refer to step S3.

[0176] Reconstruction module 4 is used to reconstruct the movement path of the mining vehicle based on the sound source localization data and output the reconstructed movement path of the mining vehicle. For details, please refer to step S4.

[0177] The positioning device for the movement path of a deep-sea mining vehicle provided in this application acquires acoustic signals from the mining vehicle, seabed, underwater, and AUV tracking the mining vehicle via an acquisition module. A preprocessing module preprocesses the acoustic signals from the mining vehicle, seabed, and underwater to reduce noise or disturbances and improve the accuracy of subsequent movement path reconstruction. The preprocessed acoustic signals and the AUV tracking the mining vehicle are then sent to a processing module for positioning processing to accurately acquire sound source location data, providing data reference for obtaining an accurate movement path. Finally, a reconstruction module reconstructs the movement path of the deep-sea mining vehicle to achieve high-precision movement path monitoring.

[0178] This invention also provides an electronic device, such as... Figure 5 As shown, the electronic device may include a processor 51 and a memory 52, wherein the processor 51 and the memory 52 may be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0179] Processor 51 can be a central processing unit (CPU). Processor 51 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0180] Memory 52, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the deep-sea mining vehicle movement path positioning method in this embodiment of the invention (e.g., Figure 4 The acquisition module 1, preprocessing module 2, processing module 3, and reconstruction module 4 are shown. The processor 51 executes various functional applications and data processing by running non-transitory software programs, instructions, and modules stored in the memory 52, thereby realizing the positioning method for the movement path of the deep-sea mining vehicle in the above method embodiment.

[0181] The memory 52 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 51, etc. Furthermore, the memory 52 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 52 may optionally include memory remotely located relative to the processor 51, and these remote memories may be connected to the processor 51 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0182] The one or more modules are stored in the memory 52, and when executed by the processor 51, they perform the following: Figure 3 The method for locating the movement path of a deep-sea mining vehicle in the illustrated embodiment.

[0183] For specific details regarding the aforementioned electronic devices, please refer to the relevant documentation. Figure 3 The relevant descriptions and effects in the illustrated embodiments are for understanding purposes only and will not be repeated here.

[0184] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0185] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method of positioning a path of movement of a deep sea mining vehicle, characterized by, The method comprises the following steps: acquiring mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals; preprocessing the mining vehicle sound wave signals, seabed sound wave signals and water sound wave signals, and outputting the preprocessed mining vehicle sound wave signals, seabed sound wave signals and water sound wave signals; using the preprocessed mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals to locate sound source signals, and outputting sound source positioning data, wherein the sound source positioning data comprises sound source intensity, sound source distance and sound source three-dimensional coordinate positioning, and the using the preprocessed mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals to locate sound source signals, and outputting sound source positioning data comprises: calculating the sound source intensity of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals based on a target function; calculating the sound source distance of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals based on the initial sound source intensity of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals, the current received sound source intensity of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals and a propagation loss factor by using the target function; based on the sound source intensity, the sound source distance and the time delay data of the signal transmission of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals, performing sound source three-dimensional coordinate positioning of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals; based on the sound source positioning data, reconstructing the motion path of the mining vehicle and outputting the reconstructed motion path of the mining vehicle.

2. The method of positioning a deep sea mining vehicle motion path according to claim 1, wherein, The preprocessing of the mining vehicle sound wave signals, seabed sound wave signals and water sound wave signals comprises extracting target signal wave bands in the mining vehicle sound wave signals, seabed sound wave signals and water sound wave signals by using a band-pass filter.

3. The method according to claim 1, wherein The target function is used to calculate the sound source intensity of the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal and the sound wave signal of the AUV tracking the mining vehicle respectively, and the sound source intensity expression is: Wherein, L(r) represents the sound source intensity of any one of the obtained mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and sound wave signal of the AUV tracking the mining vehicle, with unit of dB; L(r) is the sound source intensity of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and sound wave signal of the AUV tracking the mining vehicle, with unit of dB; L(r) is the sound source intensity of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and sound wave signal of the AUV tracking the mining vehicle, with unit of dB; L(r) is the sound source intensity of any one of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal and sound wave signal of the AUV tracking the mining vehicle, with unit of dB; 4. The method of positioning a mining vehicle path of claim 3, wherein, The expression for calculating the sound source distance of the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal and the sound wave signal of the AUV tracking the mining vehicle by the target function is: Wherein, L 0 is the initial signal intensity of any one of the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal and the sound wave signal of the AUV tracking the mining vehicle at the signal source, unit: dB; is the signal intensity of any one of the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal and the sound wave signal of the AUV tracking the mining vehicle obtained, unit: dB, is a propagation loss factor.

5. The method of positioning a deep sea mining vehicle motion path according to claim 3, wherein, The expression for positioning the three-dimensional coordinates of the sound source of the mining vehicle sound wave signal, seabed sound wave signal, underwater sound wave signal, and AUV tracking mining vehicle sound wave signal is: ; ； ； ； ； ； wherein, r i is the transmission distance of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle , , is the acoustic source coordinate of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, , , is the acoustic source coordinate of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, TE represents the error, is the signal time delay of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, is the sound speed in water, unit: meter / second, usually determined according to the temperature, salinity and depth conditions of water, is the Jacobian matrix, is the estimated current position of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, r is the bias vector, is the weight of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, is the measurement error of any of the mining vehicle acoustic signal, the seabed acoustic signal, the underwater acoustic signal and the acoustic signal of the AUV tracking the mining vehicle, TE wls minimizes the weighted error function.

6. The method of claim 3, wherein, before calculating the sound source distance of the mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals, time difference correction is performed.

7. The method of claim 1, wherein, before reconstructing the motion path of the mining vehicle based on the sound source positioning data and outputting the reconstructed motion path of the mining vehicle, the sound source intensity, sound source distance and three-dimensional coordinates of the sound source are verified.

8. The method of claim 1, wherein, The reconstruction of the motion path of the mining vehicle based on the sound source positioning data comprises at least one of real-time position reconstruction, motion distance reconstruction, motion process reconstruction, collection intensity reconstruction and collection process reconstruction of the mining vehicle.

9. A positioning device for a deep sea mining vehicle movement path, characterized in that, The method comprises the following steps: an acquisition module is configured to acquire mining vehicle sound wave signals, seabed sound wave signals, water sound wave signals and AUV tracking mining vehicle sound wave signals; The preprocessing module is configured to preprocess the mining vehicle sound wave signal, the seabed sound wave signal, and the underwater sound wave signal, and output the preprocessed mining vehicle sound wave signal, the seabed sound wave signal, and the underwater sound wave signal. The processing module is configured to use the preprocessed mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the AUV tracking mining vehicle sound wave signal to perform sound source signal positioning, and output sound source positioning data, wherein the sound source positioning data includes sound source intensity, sound source distance, and three-dimensional coordinates of the sound source. The processing module is configured to use the preprocessed mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the AUV tracking mining vehicle sound wave signal to perform sound source signal positioning, and output sound source positioning data, wherein the sound source positioning data includes sound source intensity, sound source distance, and three-dimensional coordinates of the sound source. The processing module is configured to use the preprocessed mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the AUV tracking mining vehicle sound wave signal to perform sound source signal positioning, and output sound source positioning data, wherein the sound source positioning data includes sound source intensity, sound source distance, and three-dimensional coordinates of the sound source. The processing module is configured to use the preprocessed mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the AUV tracking mining vehicle sound wave signal to perform sound source signal positioning, and output sound source positioning data, wherein the sound source positioning data includes sound source intensity, sound source distance, and three-dimensional coordinates of the sound source. The reconstruction module is configured to reconstruct the motion path of the mining vehicle based on the sound source positioning data, and output the reconstructed motion path of the mining vehicle.

10. A positioning system for a deep sea mining vehicle movement path, characterized in that, The first sensor is arranged on the mining vehicle and configured to send a noise signal. The second sensor is arranged at the seabed end and configured to obtain the mining vehicle sound wave signal output from the seabed end. The third sensor is arranged on the seabed surface and configured to obtain the seabed sound wave signal output from the seabed. The fourth sensor is arranged in the water body and maintains a predetermined distance from the seabed end, and is configured to obtain the underwater sound wave signal output from the water. The fifth sensor is arranged on the AUV and configured to collect and output the AUV tracking mining vehicle sound wave signal. The positioning device is in communication connection with the second sensor, the third sensor, the fourth sensor, and the fifth sensor, and is configured to obtain the mining vehicle sound wave signal, the seabed sound wave signal, the underwater sound wave signal, and the AUV tracking mining vehicle sound wave signal, and perform the positioning method of the motion path of the deep-sea mining vehicle according to any one of claims 1-8. ​

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