A collaborative positioning method and system for mine topographic surveying

Abstract

This invention relates to the field of measurement technology and discloses a collaborative positioning method for mine topographic surveying. The method includes: receiving monitoring data acquired by a drone hovering above the mine; transmitting corresponding ultra-wideband pulse signals to an ultra-wideband base station at the drone hovering above the mine via an ultra-wideband tag installed on the drone; calculating the relative positional relationship between the drone and the drone at the ultra-wideband base station based on the acquired ultra-wideband pulse signals; and determining the optimized positioning information of the drone based on the positional relationship, the positioning data detected by the drone, and altitude information. This collaborative positioning method for mine topographic surveying does not solely rely on satellite positioning; through the collaboration of the drone and the drone, it can adapt to various complex terrains and signal environments within the mine.

Description

Technical Field

[0001] This invention relates to the field of measurement technology, and specifically to a collaborative positioning method and system for mine topographic surveying. Background Technology

[0002] Currently, abandoned mines are mostly located in remote mountainous areas with poor network communication environments. After abandonment, the mine tops are covered with vegetation, and the mines contain accumulated water. The top and walls of the mines can be mapped using existing UAV aerial surveying methods without image control, while unmanned survey vessels (USVs) equipped with depth sounders can conduct underwater measurements. The working principle of the USV depth sounding system is to obtain high-precision planar coordinates by acquiring differential data from shore-based or network base stations through a BeiDou satellite positioning module within the vessel. This is combined with high-precision water depth data obtained through single-beam echo sounding technology to obtain high-precision three-dimensional coordinate data of underwater measurement points. However, due to terrain conditions, abandoned mines often have a large drop between the water surface and the mine top. This makes it impossible to set up shore-based base stations, or base stations may be obstructed by terrain. Furthermore, the USV's satellite positioning module may receive poor satellite signals due to terrain obstruction, resulting in a limited number of satellites being counted together with shore-based or network base stations, thus failing to obtain high-precision position coordinates and ultimately leading to measurement errors. Therefore, how to solve the problem of accurate positioning of USVs in the special geographical environment of mines has become a pressing technical issue for those skilled in the art. Summary of the Invention

[0003] To address the aforementioned shortcomings, this invention discloses a collaborative positioning method for mine topographic surveying, which solves the problem of difficult positioning of unmanned vessels in mines through dynamic reference stations and fusion algorithms.

[0004] The first aspect of this invention discloses a cooperative positioning method in mine topographic surveying, comprising:

[0005] Receive satellite positioning signals obtained through the positioning module of the unmanned vessel. If it is detected that the current unmanned vessel is in a state of satellite lock-off, proceed to the next step.

[0006] The system receives monitoring data acquired by a drone hovering above the mine pit. The monitoring data includes positioning data detected by the positioning module and height information detected by the laser altimeter, wherein the height information is the height of the drone above the water surface.

[0007] The UWB tag installed on the unmanned vessel sends a corresponding UWB pulse signal to the UWB base station of the UAV hovering above the mine pit. The UWB base station calculates the relative positional relationship between the UAV and the unmanned vessel based on the acquired UWB pulse signal, and sends the relative positional relationship between the UAV and the unmanned vessel, the positioning data detected by the positioning module, and the height information detected by the laser altimeter to the corresponding unmanned vessel through the communication module.

[0008] Based on the aforementioned positional relationships, the positioning data detected by the UAV, and the altitude information, the corresponding optimized positioning information for the unmanned vessel is determined.

[0009] As an optional implementation, in the first aspect of the present invention, after receiving the satellite positioning signal obtained by the positioning module of the unmanned vessel, the method further includes:

[0010] The corresponding satellite weight parameters are determined based on the number of visible satellites and the position accuracy factor.

[0011] The corresponding ultra-wideband weight parameters are determined based on the signal-to-noise ratio parameters and distance effectiveness of the acquired ultra-wideband signals.

[0012] The corresponding inertial measurement weight parameters are determined based on the acquired satellite availability and the motion state information of the unmanned vessel.

[0013] The position detection status of the unmanned vessel is determined based on the satellite weight parameters, ultra-wideband weight parameters, and inertial measurement weight parameters.

[0014] As an optional implementation, in the first aspect of the present invention, the cooperative localization method further includes:

[0015] The innovation value is detected by chi-square test. If the innovation value exceeds the threshold, the satellite weight parameter is reduced.

[0016] Detect the presence of multipath interference with ultra-wideband signals; if so, dynamically reduce the ultra-wideband weight parameters.

[0017] When the speed estimate remains below the threshold, it will be forced to enter the zero-speed correction mode.

[0018] As an optional implementation, in the first aspect of the present invention, the cooperative localization method further includes:

[0019] When the unmanned vessel is not in a state of unlocking, the state vector features are constructed based on the original satellite coordinates, and the initialized state vector and covariance matrix are obtained.

[0020] Based on the current position, triaxial acceleration, and time interval, state prediction and covariance prediction are performed to obtain the corresponding predicted state information and predicted covariance matrix; among them, each sensor is clock-aligned using timestamps;

[0021] Multi-source observation data is acquired, including satellite observation data, inertial navigation data, and ultra-wideband ranging data;

[0022] For each observation, the Kalman gain is calculated to update the state and obtain optimized observation parameters, and the optimized unmanned surface vessel coordinates are output.

[0023] As an optional implementation, in the first aspect of the present invention, before receiving the monitoring data acquired by the drone hovering above the mine pit, the method further includes:

[0024] Before collaborative positioning, aerial surveying is conducted using UAVs to obtain orthophotos of the mine pit and a corresponding 3D model of the mine pit. Based on the orthophotos and 3D model of the mine pit, a corresponding measurement route is determined, which includes the measurement travel route and the hovering point of the UAV.

[0025] The drone and unmanned vessel conduct mine terrain surveys according to the survey route, and the drone hovers at the hovering point to serve as a signal base station.

[0026] As an optional implementation, in the first aspect of the present invention, after using a UAV to conduct aerial surveys to obtain orthophotos of the mine pit and the corresponding three-dimensional model of the mine pit, the method further includes:

[0027] The number of matching drones is determined based on the mine conditions obtained from aerial surveys; if the mine conditions match the first condition, then one drone is used for subsequent terrain surveying.

[0028] If the mine conditions match the second condition, at least three drones are used for terrain surveying, with one drone serving as the primary drone and the other two as secondary drones. The primary drone hovers at a first altitude to provide a reference signal, and the secondary drones hover at a second altitude to relay the signal. The primary drone and the secondary drones communicate via ultra-wideband signals.

[0029] As an optional implementation, in the first aspect of the present invention, the cooperative localization method further includes:

[0030] Extend signal coverage by deploying repeater poles at high points;

[0031] After determining the optimized positioning information of the corresponding unmanned vessel, the process also includes:

[0032] The unmanned surface vessel performs fusion calculations based on the acquired multi-source data to obtain the three-dimensional coordinates of underwater points and generates a digital elevation model of the underwater terrain for data stitching with the surface model.

[0033] A second aspect of this invention discloses a cooperative positioning system for mine topographic surveying, comprising:

[0034] First receiving module: used to receive satellite positioning signals obtained by the positioning module of the unmanned vessel. If it is detected that the current unmanned vessel is in a state of satellite lock-off, then proceed to the next step.

[0035] The second receiving module is used to receive monitoring data acquired by a drone hovering above the mine pit. The monitoring data includes positioning data detected by the positioning module and height information detected by the laser altimeter, wherein the height information is the height of the drone above the water surface.

[0036] Ranging module: Used to send corresponding ultra-wideband pulse signals to the ultra-wideband base station of the UAV hovering above the mine pit through the ultra-wideband tag set on the UAV. At the ultra-wideband base station, the relative position relationship between the UAV and the UAV is calculated based on the acquired ultra-wideband pulse signals. The relative position relationship between the UAV and the UAV, the positioning data detected by the positioning module, and the height information detected by the laser altimeter are sent to the UAV through the communication module.

[0037] Positioning optimization module: used to determine the corresponding optimized positioning information of the unmanned vessel based on the positional relationship, the positioning data detected by the UAV, and the altitude information.

[0038] A third aspect of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the collaborative positioning method in mine topographic surveying disclosed in the first aspect of the present invention.

[0039] A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the collaborative positioning method in mine topographic surveying disclosed in the first aspect of the present invention.

[0040] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0041] The collaborative positioning method for mine topographic surveying in this invention does not solely rely on satellite positioning. Through the collaboration of unmanned surface vessels (USVs) and drones, it can adapt to various complex terrains and signal environments within the mine. Whether in open areas or areas with severe signal obstruction, effective positioning can be achieved through the collaboration of these two methods, improving the adaptability of the measurement system to different mine environments and making the measurement work more flexible and efficient. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1This is a flowchart illustrating the collaborative positioning method in mine topographic surveying disclosed in an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of the time synchronization mechanism disclosed in an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the structure of the multi-UAV relay network disclosed in an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of a collaborative positioning system for mine topographic surveying provided in an embodiment of the present invention;

[0047] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] It should be noted that the terms "first," "second," "third," "fourth," etc., in the specification and claims of this invention are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, in the embodiments of this invention are intended to cover non-exclusive inclusion. Exemplarily, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0050] The working principle of an unmanned surface vessel (USV) depth sounding system is to obtain high-precision planar coordinates by acquiring differential data from shore-based or network base stations using a BeiDou satellite positioning module within the vessel. This high-precision water depth is then combined with single-beam echo sounding technology to obtain high-precision three-dimensional coordinate data for underwater measurement points. Often, in abandoned mines, due to terrain conditions, there is a large drop between the water surface and the mine top. Shore-based base stations cannot be set up, or the base stations are obstructed by terrain. The USV's satellite positioning module receives poor satellite signals due to terrain obstruction, resulting in a limited number of satellites being counted together with the shore-based or network base stations, thus failing to obtain high-precision position coordinates and ultimately leading to measurement errors. Based on this, this invention discloses a collaborative positioning method, system, electronic equipment, and storage medium for mine topographic surveying. It does not solely rely on satellite positioning; through the collaboration of USVs and drones, it can adapt to various complex terrains and signal environments within mines. Whether in open areas or areas with severe signal obstruction, effective positioning can be achieved through the collaboration of both, improving the adaptability of the measurement system to different mine environments and making measurement work more flexible and efficient.

[0051] Example 1

[0052] Please see Figure 1 , Figure 1 This is a flowchart illustrating the collaborative positioning method in mine topographic surveying disclosed in this invention. The execution entity of the method described in this embodiment is an entity composed of software and / or hardware. This entity can receive relevant information via wired or / or wireless means and can send certain instructions. It may also have certain processing and storage functions. This entity can control multiple devices, such as remote physical servers or cloud servers and related software, or local hosts or servers and related software that perform related operations on devices located at a certain location. In some scenarios, multiple storage devices can also be controlled; these storage devices may be placed in the same location as the devices or in different locations. Figures 1 to 3 As shown, the cooperative localization method based on mine topographic surveying includes the following steps:

[0053] S101: Receive satellite positioning signals obtained through the positioning module of the unmanned vessel. If it is detected that the current unmanned vessel is in a state of satellite lock-off, proceed to the next step.

[0054] S102: Receive monitoring data obtained by a drone hovering above the mine pit. The monitoring data includes positioning data detected by the positioning module and height information detected by the laser altimeter, wherein the height information is the height information of the drone above the water surface.

[0055] S103: The UWB tag set on the unmanned vessel sends the corresponding UWB pulse signal to the UWB base station of the UAV hovering above the mine pit. The UWB base station calculates the relative position relationship between the UAV and the unmanned vessel based on the obtained UWB pulse signal, and sends the relative position relationship between the UAV and the unmanned vessel, the positioning data detected by the positioning module, and the height information detected by the laser altimeter to the corresponding unmanned vessel through the communication module.

[0056] S104: Determine the optimized positioning information of the unmanned vessel based on the positional relationship, the positioning data detected by the UAV, and the altitude information.

[0057] In actual measurement processes, the complex environment of mine pits makes satellite signals susceptible to obstruction, often resulting in unmanned surface vessel (USV) satellite positioning losing lock. This method, upon detecting a loss of satellite lock on the USV, utilizes the positioning data and altitude information of the unmanned aerial vehicle (UAV), as well as the relative positional relationship between the USV and the UAV, to determine the USV's location. This effectively solves the positioning problem caused by satellite signal loss and ensures the continuity of positioning.

[0058] The UAV positioning module in this embodiment of the invention can acquire accurate positioning data, the laser altimeter can accurately measure its height above the water surface, and ultra-wideband technology can calculate the relative position of the UAV and the unmanned surface vessel with high precision. By fusing this information, the positioning accuracy of the unmanned surface vessel in the mine can be significantly improved, providing more accurate location data for mine topographic surveying, which helps to generate a more accurate terrain model and provides a reliable basis for subsequent resource extraction, slope monitoring, and other work. This method does not rely solely on satellite positioning; through the collaboration of the unmanned surface vessel and the UAV, it can adapt to various complex terrains and signal environments within the mine. Whether in open areas or areas with severe signal obstruction, effective positioning can be achieved through the collaboration of the two, improving the adaptability of the measurement system to different mine environments and making the measurement work more flexible and efficient. Using unmanned surface vessels and UAVs for collaborative positioning enables automated measurement, reduces human intervention, and lowers the risk of surveyors working in hazardous environments. At the same time, unmanned equipment can quickly acquire data and transmit it in real time, greatly improving measurement efficiency compared to traditional measurement methods and enabling faster completion of mine topographic surveying tasks.

[0059] More preferably, after receiving the satellite positioning signal acquired by the positioning module of the unmanned vessel, the method further includes:

[0060] The corresponding satellite weight parameters are determined based on the number of visible satellites and the position accuracy factor.

[0061] The corresponding ultra-wideband weight parameters are determined based on the signal-to-noise ratio parameters and distance effectiveness of the acquired ultra-wideband signals.

[0062] The corresponding inertial measurement weight parameters are determined based on the acquired satellite availability and the motion state information of the unmanned vessel.

[0063] The position detection status of the unmanned vessel is determined based on the satellite weight parameters, ultra-wideband weight parameters, and inertial measurement weight parameters.

[0064] The solution in this embodiment of the invention achieves differentiated evaluation of different positioning data sources (satellite positioning, ultra-wideband relative positioning, and inertial measurement) by calculating satellite weight parameters, ultra-wideband weight parameters, and inertial measurement weight parameters respectively.

[0065] The satellite weight parameter in this embodiment combines the number of visible satellites and the Position Precision Factor (PDOP) to accurately reflect the reliability of satellite positioning (e.g., when there are few visible satellites and the PDOP value is high, the satellite weight decreases); when the number of satellites is ≥4 and PDOP <6, the weight increases linearly with the increase of the number of satellites and decreases exponentially with the increase of PDOP. For example: number of satellites = 8, PDOP = 1.5 → sat_weight ≈ 1.0;

[0066] Number of satellites = 5, PDOP = 4.0 → sat_weight ≈ 0.5;

[0067] Satellite count = 3 → sat_weight = 0.0 (force satellite data disabled).

[0068] In this embodiment of the invention, the ultra-wideband weight parameter is based on the signal-to-noise ratio (SNR) and distance effectiveness to determine the stability of the ultra-wideband signal (e.g., when the SNR is low or the distance calculation is abnormal, the weight is reduced). When the UWB signal has a high SNR (SNR>20dB) and the distance is short (<500 meters), the weight is close to 1.0. If multipath interference is detected (SNR drops sharply), the weight is automatically reduced (e.g., SNR=5dB→uwb_weight≈0.4). When the distance exceeds 800 meters, the weight is reduced to zero (outside the effective range of UWB).

[0069] In this embodiment of the invention, the inertial measurement weight parameter is correlated with satellite availability and the motion state of the unmanned vessel (UV). (For example, when the satellite is lost and the motion is violent, the risk of inertial measurement drift is high, and the weight is reduced.) When the satellite fails: the IMU weight increases to 0.7, becoming the primary positioning source; in a stationary state: even if the satellite is available, the IMU weight decreases to 0.1 (to avoid cumulative errors); in normal motion: an auxiliary weight of 0.3 is maintained. Based on the comprehensive judgment of the UV's position detection status based on the three types of weight parameters, the reliability of the current positioning data can be more accurately identified, avoiding the impact of errors from a single data source on the positioning results.

[0070] The solution in this invention dynamically adjusts the weights of different positioning methods, enabling the system to adapt to changes in the mining environment. For example, when satellite signals are strong, satellite weight is high, prioritizing high-precision satellite positioning; when satellite signals weaken or lose lock, the weights of ultra-wideband (UWB) and inertial measurement (IGM) are automatically increased (if their signals are stable), compensating for the deficiencies of a single data source through multi-source data fusion; when UWB signals are obstructed or interfered with, their weight is reduced to minimize error propagation. This dynamic weighting mechanism significantly improves the system's anti-interference capability in complex mining environments (such as signal abrupt changes and multipath interference), ensuring continuous and stable positioning.

[0071] In practical implementation, data sources with high reliability are assigned higher confidence levels and directly used for positioning results. Data with low reliability is corrected by combining historical trajectories and multi-source verification to further improve the accuracy and reliability of the final positioning information. Through comprehensive evaluation of multi-dimensional parameters (number of visible satellites, PDOP, signal-to-noise ratio, motion status, etc.), the problem of misjudging the positioning status by a single indicator is avoided (such as misjudging positioning failure simply because of a low number of satellites, ignoring the high stability of ultra-wideband signals at this time). This makes the system's judgment of the positioning status more objective and comprehensive, providing a guarantee for the efficient operation of collaborative positioning.

[0072] More preferably, the cooperative localization method further includes:

[0073] The innovation value is detected by chi-square test. If the innovation value exceeds the threshold, the satellite weight parameter is reduced.

[0074] Detect the presence of multipath interference with ultra-wideband signals; if so, dynamically reduce the ultra-wideband weight parameters.

[0075] When the speed estimate remains below the threshold, it will be forced to enter the zero-speed correction mode.

[0076] The solution of this invention can improve anti-interference capability and reduce the impact of abnormal data. The innovation value (the deviation between the measured value and the predicted value) is detected by chi-square test. When the innovation value exceeds the threshold, it indicates that there may be anomalies in the satellite positioning data (such as signal jumps, multipath errors, etc.). At this time, reducing the satellite weight parameter can reduce the interference of abnormal data on the final positioning result and avoid positioning drift caused by sudden changes in satellite signals.

[0077] For ultra-wideband (UWB) signals, buildings and rock walls in the mining environment can easily cause multipath interference (signals are received after reflection, leading to distance calculation errors). By detecting multipath interference and dynamically reducing the UWB weight parameters, the errors caused by such interference can be effectively suppressed, ensuring that UWB data can play its full role when reliable and reducing its impact when abnormal.

[0078] Optimizing positioning accuracy in low-speed / stationary states is crucial. When the estimated speed of an unmanned surface vessel (USV) remains below a threshold (e.g., during low-speed navigation or temporary stationary states), the inertial measurement unit (IMU) is prone to positioning drift ("zero-speed drift") due to accumulated integration errors. By forcibly entering zero-speed correction mode, the constraint of zero speed can be used to calibrate the inertial measurement data, eliminating accumulated errors and significantly improving the positioning accuracy of the USV in low-speed or stationary states. This avoids trajectory deviation caused by prolonged low-speed movement and ensures accurate and reliable location data for key points (such as depressions at the bottom of the pit and slope edges) in mine topographic surveys.

[0079] The above strategy achieves triggered dynamic adjustment of weight parameters and working modes by real-time monitoring of abnormal features during the positioning process (excessive innovation value, multipath interference, low speed state). This enables the positioning system to quickly adapt to the complex and ever-changing environment in the mine (such as sudden signal blockage, prominent multipath effects in local areas, and unmanned vessels slowing down due to terrain limitations). It avoids the one-size-fits-all problem of fixed weights or modes, making the positioning data fusion more in line with the actual scenario and improving the overall robustness of the system.

[0080] Targeted measures are taken to address the deficiencies of different data sources (satellite signal anomalies, ultra-wideband multipath, and low-speed inertial drift). When a single data source malfunctions, its weight can be reduced or the correction mode switched to prioritize other reliable data sources, ensuring uninterrupted positioning. For example, when satellite signals are abnormal, their weight is reduced, while the roles of ultra-wideband and inertial measurements (after zero-speed correction) are enhanced, thereby maintaining positioning continuity and providing stable position support for the efficient conduct of mine topographic surveys.

[0081] More preferably, the cooperative localization method further includes:

[0082] When the unmanned vessel is not in a state of unlocking, the state vector features are constructed based on the original satellite coordinates, and the initialized state vector and covariance matrix are obtained.

[0083] Based on the current position, triaxial acceleration, and time interval, state prediction and covariance prediction are performed to obtain the corresponding predicted state information and predicted covariance matrix; among them, each sensor is clock-aligned using timestamps;

[0084] Multi-source observation data is acquired, including satellite observation data, inertial navigation data, and ultra-wideband ranging data;

[0085] For each observation, the Kalman gain is calculated to update the state and obtain optimized observation parameters, and the optimized unmanned surface vessel coordinates are output.

[0086] In this embodiment of the invention, when the unmanned surface vessel (USV) is not lost lock, a state vector feature is constructed using the original satellite coordinates, and the state vector and covariance matrix are initialized. This provides a reliable initial reference for subsequent positioning calculations, avoiding cumulative errors caused by initial value deviations. By combining the current position state, three-axis acceleration, and time interval for state prediction and covariance prediction, the position change trend of the USV can be predicted based on kinematic laws. This provides a priori reference for multi-source data fusion, reduces the impact of sudden changes in observation data on positioning results, and improves the smoothness of positioning.

[0087] By aligning the clocks of each sensor (satellite positioning module, inertial navigation device, and ultra-wideband module) with timestamps, the time difference in data acquisition from different devices is eliminated, ensuring the consistency of satellite observation data, inertial navigation data, and ultra-wideband ranging data in the time dimension. This lays the foundation for accurate fusion of multi-source data. The comprehensive utilization of multi-source observation data (satellite data provides absolute coordinates, inertial data reflects motion attitude, and ultra-wideband data provides relative distance) can compensate for the limitations of a single data source (such as satellite signal fluctuations, inertial drift, and ultra-wideband range limitations), improving the redundancy and reliability of positioning through data complementarity.

[0088] The Kalman gain is calculated and the state is updated for each observation data point. The weight of each data source in the fusion result is dynamically adjusted based on its real-time accuracy (reflected by the covariance matrix). Higher-accuracy data receives a higher gain and has a greater impact on the final result; lower-accuracy data receives a lower gain to reduce error propagation. This adaptive adjustment mechanism makes the fused observation parameters closer to the real state, significantly improving the optimization accuracy of the unmanned surface vessel's coordinates.

[0089] The optimized coordinate output combines the advantages of absolute positioning, relative positioning, and motion continuity. Especially when satellite signals are good but there is local interference, it can avoid positioning jumps and ensure the stability of coordinate output by supplementing and correcting with inertial and ultra-wideband data.

[0090] This process retains multi-source data fusion logic even when the unmanned vessel is not locked, rather than solely relying on satellite positioning. Even when satellite signals are in a critical state of decreased accuracy despite not being locked (e.g., a low number of visible satellites or a high PDOP value), high positioning accuracy can be maintained through auxiliary corrections from inertial navigation and ultra-wideband data. The dynamic updating of the covariance matrix reflects the changing trend of positioning errors in real time. When the accuracy of a data source decreases, such as when the ultra-wideband signal is interfered with, its corresponding covariance increases, and the Kalman gain automatically decreases, thereby reducing the impact of that data on the results and enabling the system to maintain stable positioning performance even in complex environments.

[0091] The solution of this invention complements the aforementioned mechanisms for handling lost-lock states and dynamic weight adjustment, constructing a positioning fusion framework covering all scenarios from normal to critical to lost-lock: under normal conditions, Kalman filtering is used to achieve refined fusion of multi-source data; under critical conditions, weight adjustment is used to suppress abnormal data; and under lost-lock conditions, UAV collaboration and inertial correction are relied upon to ensure the positioning accuracy and continuity of the unmanned vessel in the entire mining scenario.

[0092] More preferably, before receiving the monitoring data acquired by the drone hovering above the mine, the method further includes:

[0093] Before collaborative positioning, aerial surveying is conducted using UAVs to obtain orthophotos of the mine pit and a corresponding 3D model of the mine pit. Based on the orthophotos and 3D model of the mine pit, a corresponding measurement route is determined, which includes the measurement travel route and the hovering point of the UAV.

[0094] The drone and unmanned vessel conduct mine terrain surveys according to the survey route, and the drone hovers at the hovering point to serve as a signal base station.

[0095] In this embodiment of the invention, the solution requires pre-generated orthophotos and 3D models of the mine pit from aerial surveys conducted by UAVs. These models visually reflect the overall topography and geomorphological features of the mine pit (such as slope orientation, water distribution, and obstacle locations). Based on this data, a measurement route is planned (including the UAV's travel route and the UAV's hovering points). This ensures that the UAV's path covers key measurement areas (such as areas with dramatic terrain changes and key monitoring points), while preventing the UAV from running aground or colliding due to complex terrain (such as shallows or reefs). The appropriate setting of the UAV's hovering points (such as locations with minimal signal obstruction and wide coverage) ensures stable ultra-wideband signal transmission and reliable positioning benchmarks. This advance planning makes the collaborative operation of UAVs and UAVs more targeted, reduces ineffective navigation and redundant measurements, and significantly improves measurement efficiency.

[0096] Specifically, the hovering points of the UAVs, which serve as signal base stations, are determined through 3D model planning. This avoids signal obstruction sources within the mine (such as tall rock walls and buildings), ensuring a smoother ultra-wideband signal transmission path between the UAVs and the unmanned surface vessel (USV) and reducing multipath interference. At the same time, the distribution of hovering points can be gridded according to the mine terrain, enabling the USV to maintain effective communication with at least one UAV hovering point at any location on the measurement route. This avoids positioning failures caused by signal interruption at a single hovering point, enhancing the baseline stability and redundancy of collaborative positioning.

[0097] In this embodiment of the invention, the pre-acquired 3D model of the mine pit contains accurate terrain elevation information, which can be used as terrain constraints for subsequent positioning. For example, when there is a significant contradiction between the positioning result of the unmanned vessel and the terrain features in the 3D model (such as the actual water depth in a certain area being shallow), the positioning information can be corrected by combining the model data to reduce positioning deviations caused by sensor errors (such as inertial drift and ultra-wideband ranging bias). At the same time, the measurement route is planned based on the 3D model, which can ensure that the unmanned vessel's trajectory conforms to the actual terrain, making the collected terrain data more consistent with the preset route, and the final measurement results (such as underwater terrain models) have better accuracy.

[0098] Mining environments often present hidden dangers (such as underwater obstacles and rockfall areas on slopes). Pre-survey drones can identify these risky areas and proactively avoid them when planning the survey route. Unmanned surface vessels (USVs) can reduce the probability of accidentally entering dangerous areas by following planned routes, and drones operating at pre-set hovering points can avoid high-risk airspace (such as unstable areas above slopes), thereby reducing the risk of equipment damage and improving the operational safety of the entire surveying system.

[0099] The solution in this invention combines global aerial survey planning with local collaborative positioning to form a complete measurement logic: first, the overall topography of the mine pit is grasped through UAV aerial surveying; then, local operational details are planned based on the global information; finally, unmanned surface vessels and UAVs perform collaborative positioning measurements according to the plan. This framework avoids the inefficiency and chaos of the traditional exploration-and-measurement mode, making mine pit topography measurement more systematic and scientific, providing a unified spatial benchmark for subsequent data stitching, terrain modeling, and other stages, and improving the consistency and reliability of the overall measurement results.

[0100] More preferably, after using a drone to conduct aerial surveys to obtain orthophotos of the mine pit and the corresponding 3D model of the mine pit, the method further includes:

[0101] The number of matching drones is determined based on the mine conditions obtained from aerial surveys; if the mine conditions match the first condition, then one drone is used for subsequent terrain surveying.

[0102] If the mine conditions match the second condition, at least three drones are used for terrain surveying, with one drone serving as the primary drone and the other two as secondary drones. The primary drone hovers at a first altitude to provide a reference signal, and the secondary drones hover at a second altitude to relay the signal. The primary drone and the secondary drones communicate via ultra-wideband signals.

[0103] This invention matches the number of drones based on mine conditions obtained from aerial surveys (such as mine size, terrain complexity, and signal obstruction), thus avoiding resource waste or insufficient configuration.

[0104] For mines that meet the first condition (such as small size, simple terrain, and no obvious signal obstruction areas), only one drone can serve as a signal base station, reducing equipment investment and energy consumption and improving measurement economy. For mines that meet the second condition (such as large mines, complex terrain, and multiple signal obstruction areas), at least three drones working together can cover a wider area and solve signal transmission problems, ensuring that positioning needs in complex environments are met.

[0105] The present invention employs a division of labor mode combining a main UAV and an auxiliary UAV (the main UAV provides a reference signal at a first altitude, and the auxiliary UAV relays the signal at a second altitude). This effectively solves the signal obstruction problem in the mine. The high-altitude hovering of the main UAV reduces the obstruction of its own positioning signal (such as satellite signal), ensuring the accuracy of the reference positioning data. The auxiliary UAV, as a relay node, can transmit the main UAV's signal to unmanned surface vessels (USVs) that are obstructed by rock walls or obstacles, or receive ultra-wideband signals sent by USVs in blind spots and forward them to the main UAV, eliminating "dead zones" in signal transmission and ensuring that USVs can maintain stable communication with UAVs in all areas of the mine (especially in complex terrain), avoiding positioning failures caused by signal interruptions.

[0106] In this embodiment of the invention, the configuration of at least three UAVs forms a multi-node collaborative positioning reference network: the master UAV provides the core reference signal, and the auxiliary UAV can serve as a backup node. When the master UAV cannot work normally due to unforeseen circumstances (such as temporary signal loss or equipment failure), it can temporarily assume the reference or relay function, thereby improving the fault tolerance of the system. At the same time, the ultra-wideband communication of multiple UAVs can achieve mutual verification, reduce the impact of measurement errors of a single UAV (such as laser altimeter deviation or positioning drift) on the overall positioning, and ensure the reliability of the reference signal.

[0107] For large, complex mines (such as those with multiple steps, deep depressions, or dense obstacles), the signal coverage and penetration of a single UAV are limited. However, the layered hovering (at different altitudes) and relay cooperation of multiple UAVs can adapt to the three-dimensional spatial structure of the mine: low-altitude auxiliary UAVs can approach complex terrain to ensure signal coverage of unmanned vessels in near-shore and shallow areas; high-altitude main UAVs can control the overall situation and achieve baseline signal coverage of the entire mine area, enabling the system to cope with the positioning challenges of various complex mine environments.

[0108] Multipath effects and electromagnetic interference within mines can easily affect the quality of ultra-wideband signal transmission. The relay function of auxiliary UAVs can shorten the transmission distance of ultra-wideband signals and reduce signal attenuation and interference. At the same time, real-time data synchronization between the main and auxiliary UAVs is achieved through ultra-wideband communication, ensuring that the position information and timestamps of each node remain consistent. This provides a more accurate collaborative benchmark for the relative positioning calculation of the unmanned vessel, further improving positioning accuracy.

[0109] The solution of this invention dynamically adjusts the number and functions of drones according to the conditions of the mine, and constructs a collaborative architecture that can be expanded on demand: lightweight configuration (single drone) in simple scenarios ensures efficiency, while multi-node configuration (main + auxiliary drones) in complex scenarios ensures performance. This enables the system to adapt to the low-cost measurement needs of small mines as well as the high-precision and high-reliability measurement requirements of large and complex mines, thus expanding the application scope of the collaborative positioning method.

[0110] More preferably, the cooperative localization method further includes:

[0111] Extend signal coverage by deploying repeater poles at high points;

[0112] After determining the optimized positioning information of the corresponding unmanned vessel, the process also includes:

[0113] The unmanned surface vessel performs fusion calculations based on the acquired multi-source data to obtain the three-dimensional coordinates of underwater points and generates a digital elevation model of the underwater terrain for data stitching with the surface model.

[0114] First, the mine's topography is analyzed to determine the locations of high points around the mine, such as high mountain peaks or building rooftops. Then, repeater poles are installed at these high points, each equipped with wireless communication relay equipment, such as wireless bridges. These devices can receive signals from drones or other signal sources and relay them to various areas within the mine, achieving signal relay transmission. The repeater poles can be powered by a combination of solar panels and batteries to achieve maintenance-free operation.

[0115] In complex mine terrain, signal blind spots are common. Deploying repeater poles at high points can extend signal transmission to areas that were previously difficult to cover, ensuring that unmanned surface vessels (USVs) can receive a stable signal from any location within the mine. This reduces signal interruptions and guarantees the normal operation of the collaborative positioning system. As fixed signal relay nodes, repeater poles provide a more stable signal transmission path compared to mobile relay devices, reducing signal fluctuations caused by changes in the UAV's flight attitude and providing reliable positioning signal support for the USV, thus improving positioning accuracy.

[0116] Specifically, the unmanned surface vessel (USV) in this embodiment of the invention is equipped with various sensors, such as a depth sounder, GPS receiver, and inertial measurement unit, to collect underwater topographic data in real time during navigation, including information such as water depth, position, and attitude. Simultaneously, it receives multi-source data, including aerial survey data from unmanned aerial vehicles (UAVs) and data from other ground control points. Using this data, and through data fusion algorithms such as Kalman filtering, the three-dimensional coordinates of underwater points are calculated. Then, using specialized geographic information system (GIS) software or surveying software, a digital elevation model (DEM) of the underwater topography is generated based on the three-dimensional coordinates of the underwater points. The surface model can be obtained from UAV aerial survey data through photogrammetric processing. Finally, through coordinate transformation and matching algorithms, the underwater topography DEM and the surface model are stitched together to form a complete integrated land-water topography model.

[0117] It can acquire complete underwater and surface topographic information of mines, providing comprehensive data support for integrated management and analysis of mines. For example, it can be used to assess the water storage capacity of mines and analyze the impact of topographic changes on the surrounding environment. Multi-source data fusion can fully utilize the advantages of each sensor, complementing and verifying each other, reducing the impact of measurement errors from a single sensor, thereby improving the accuracy of underwater topographic measurements and making the generated digital elevation model closer to the real terrain, providing a more reliable basis for subsequent engineering design and decision-making. The stitched integrated land and water topographic model can more intuitively display the overall topography of the mine, facilitating visual analysis by staff and helping to identify potential problems and risks, such as the distribution of underwater obstacles and areas of abrupt topographic changes, providing strong support for the safe operation and rational development of mines.

[0118] During implementation, the drone hovers 50-100 meters directly above the mine pit, prioritizing the use of RTK-GPS (Real-time Dynamic Differential GPS) to obtain high-precision absolute position.

[0119] (uav_pos=[X_uav,Y_uav,Z_uav]) ensures that the self-positioning error is <0.1 meters. If the satellite signal at the drone's location is also partially blocked, the position drift is corrected by fusing inertial navigation and visual odometry (such as IMU + downward-facing camera), and the self-coordinates are updated every 0.1 seconds as the origin of the dynamic reference.

[0120] This invention provides a UAV-unmanned surface vessel cooperative positioning system that solves the positioning problem through dynamic reference stations and fusion algorithms.

[0121] 1. The drone carries a module, including:

[0122] Dual-frequency RTK positioning module: Supports both BeiDou and GPS systems, with a built-in high-precision IMU.

[0123] Ultra-wideband (UWB) base station: transmits centimeter-level accuracy ranging signals (effective range 500-800 meters).

[0124] Laser altimeter: Real-time acquisition of the height of drones above the water surface

[0125] Integrated image and data communication module: Supports LoRa (long-range) + Wi-Fi (high-speed) dual channels.

[0126] 2. Unmanned surface vessel upgrade module, including:

[0127] UWB positioning tags: forming a relative positioning system with UWB base stations on drones.

[0128] Multi-source fusion positioning controller: integrates satellite positioning / UWB / IMU data processing

[0129] Underwater acoustic transducer: transmits acoustic positioning signals (backup plan)

[0130] Anti-obstruction antenna: Four-feed spiral antenna, enhancing low elevation angle signal reception.

[0131] 3. Shore-based auxiliary equipment

[0132] Portable weather station: Real-time acquisition of atmospheric delay parameters

[0133] Foldable signal repeater pole: temporarily deployed at the highest point in the mine pit.

[0134] Core localization algorithm design in this invention embodiment

[0135] # Pseudocode implementation of defawf_kf(uav_pos,usv_raw,uwb_dist,imu_data):

[0136] #Input: Drone location / Unmanned surface vessel original location / UWB distance / IMU data

[0137] #Output: Optimized unmanned surface vessel position

[0138] #1. Calculate the weight factors for each data source: sat_weight = calculate_sat_weight(satellite_num, PDOP) # Satellite weight uwb_weight = 1 - exp(-uwb_snr / 10) # UWB signal-to-noise ratio weight imu_weight = 0.7 if sat_num < 4 else 0.3 # IMU dynamic weight

[0139] #2. Construct the state vector X = [usv_raw.x,usv_raw.y,usv_raw.z,vx,vy,vz]

[0140] #3. Kalman Prediction (IMU Dominated)

[0141] X_pred=imu_prediction(X,imu_data)

[0142] #4. Multi-source observation update Z = []

[0143] ifsat_weight>0.2:

[0144] Z.append(satellite_obs())

[0145] ifuwb_dist_valid:

[0146] Z.append(uwb_range_obs(uav_pos,uwb_dist))

[0147] iflaser_alt_valid:

[0148] Z.append(surface_height_obs())

[0149] #5. Adaptive Measurement Update forobsinZ:

[0150] K = adaptive_kalman_gain(obs.weight) # Dynamically adjust the gain X = update_state(X_pred,obs,K)

[0151] returnX[0:3]# Return to the optimized position

[0152] Specifically, the dual-platform linkage workflow of this invention embodiment

[0153] Step 1: Establishing a dynamic baseline using the UAV

[0154] 1. Aerial anchoring

[0155] Hover over the mine pit (50-100m height)

[0156] RTK yields a fixed solution: $σ_{xy}=8mm+1ppm$ $σ_z=15mm+1ppm$

[0157] 2. UWB signal coverage

[0158] Transmit pulse signal (500MHz bandwidth, resistant to multipath interference)

[0159] Coverage area: Diameter of the cone-shaped area = 2 × height (100m height covers 200m of water area)

[0160] Step 2: Real-time positioning of the unmanned vessel

[0161] #Location Fusion Pseudocode

[0162] while surveying:

[0163] # Obtain UWB slant range (including carrier phase observations)

[0164] uwb_range=get_uwb_range()#Accuracy±10cm

[0165] uav_pos = receive_uav_position() # UAV coordinates

[0166] #IMU Data Decomposition

[0167] imu_delta = imu.get_displacement() # Displacement increment

[0168] #Fusion Solution (Extended Kalman Filter)

[0169] predicted_pos=prev_pos+imu_delta

[0170] measured_pos=calculate_position(uav_pos,uwb_range)

[0171] #Adaptive weighting (based on signal quality)

[0172] k = 0.7ifuwb_snr > 30 else 0.3 # UWB dominates when signal is strong

[0173] fused_pos=k*measured_pos+(1-k)*predicted_pos

[0174] #Water surface elevation constraints (from UAV laser scanning)

[0175] fused_pos.z=surface_equation(fused_pos.x, fused_pos.y)

[0176] output_position(fused_pos)

[0177] Step 3: Dynamic Error Correction

[0178] 1. Multipath interference suppression

[0179] Using a combined Time of Flight (ToF) and Angle of Arrival (AoA) calculation

[0180] $ρ=\frac{c·Δt}{2}+\frac{λ·Δφ}{2π}$

[0181] (c: speed of light, λ: wavelength, Δφ: phase difference)

[0182] Discard reflected signals: Discard signals when the signal path difference is greater than 20% of the direct path difference.

[0183] 2. IMU Zero-Rate Correction (ZUPT)

[0184] When the unmanned surface vessel's speed is <0.1 m / s:

[0185] Reset speed error: $v_x=v_y=v_z=0$

[0186] Compensate for accelerometer bias.

[0187] The system advantages of this invention include:

[0188] 1. Significant improvement in accuracy: The positioning accuracy in occluded environments is improved from the meter level to the sub-meter level, and the elevation accuracy is improved by 20 times (laser water surface modeling);

[0189] 2. Enhanced robustness: It can maintain high-precision positioning for 10 minutes after satellite loss of lock, and the IMU autonomous navigation error is <1m / 5min when UWB is interrupted;

[0190] 3. Engineering applicability: Deployment time <30 minutes (traditional shore-based base stations require 2 hours), suitable for deep mine pits with a drop >200m.

[0191] Key technical breakthroughs in the embodiments of this invention:

[0192] 1. Dynamic reference positioning technology: The drone hovers 50-100 meters directly above the mine pit, forming an aerial mobile reference station. It provides a relative positioning reference through UWB, solving the problem of satellite signal blockage.

[0193] 2. Water surface elevation constraint model: Using UAV laser altimetry data and water surface echo characteristics, a water surface elevation plane equation is constructed: Z_surface=aX+bY+c, which serves as a strong height constraint for UAV positioning and reduces vertical direction error.

[0194] 3. Robust adaptive filtering, algorithm automatically identifies abnormal observations: When the satellite loses lock, it switches to UWB / IMU dominant mode to detect UWB multipath interference (mine wall reflection) and IMU zero-speed correction to prevent error accumulation.

[0195] 4. Terrain matching-assisted positioning: A 3D model of the mine pit is generated in advance using UAV aerial surveying. When the unmanned vessel is navigating, the position correction is provided by matching the measured water depth with the model terrain.

[0196] This solution overcomes terrain limitations through dynamic air-water benchmark transfer and, combined with an adaptive multi-source fusion algorithm, maintains sub-meter positioning accuracy even in extreme conditions with no satellite signal. For practical applications, it is recommended to use a DJI M300RTK drone and an OceanAlphaSL20 depth sounding unmanned surface vessel platform. The entire system can be stored in two transport containers, making it suitable for mobile deployment in mountainous areas.

[0197] The collaborative positioning method for mine topographic surveying in this invention does not solely rely on satellite positioning. Through the collaboration of unmanned surface vessels (USVs) and drones, it can adapt to various complex terrains and signal environments within the mine. Whether in open areas or areas with severe signal obstruction, effective positioning can be achieved through the collaboration of these two methods, improving the adaptability of the measurement system to different mine environments and making the measurement work more flexible and efficient.

[0198] Example 2

[0199] Please see Figure 4 , Figure 4 This is a schematic diagram of the collaborative positioning system for mine topographic surveying disclosed in an embodiment of the present invention. Figure 4 As shown, the cooperative positioning system in this mine topographic survey may include:

[0200] First receiving module 21: Used to receive satellite positioning signals obtained by the positioning module of the unmanned vessel. If it is detected that the current unmanned vessel is in a satellite unlocked state, then proceed to the next step.

[0201] The second receiving module 22 is used to receive monitoring data acquired by a drone hovering above the mine pit. The monitoring data includes positioning data detected by the positioning module and height information detected by the laser altimeter, wherein the height information is the height information of the drone above the water surface.

[0202] Ranging module 23: Used to send corresponding ultra-wideband pulse signals to the ultra-wideband base station of the UAV hovering above the mine pit through the ultra-wideband tag set on the UAV. At the ultra-wideband base station, the relative position relationship between the UAV and the UAV is calculated based on the acquired ultra-wideband pulse signals. The relative position relationship between the UAV and the UAV, the positioning data detected by the positioning module, and the height information detected by the laser altimeter are sent to the UAV through the communication module.

[0203] Positioning optimization module 24: used to determine the corresponding optimized positioning information of the unmanned vessel based on the positional relationship, the positioning data detected by the UAV, and the altitude information.

[0204] The collaborative positioning method for mine topographic surveying in this invention does not solely rely on satellite positioning. Through the collaboration of unmanned surface vessels (USVs) and drones, it can adapt to various complex terrains and signal environments within the mine. Whether in open areas or areas with severe signal obstruction, effective positioning can be achieved through the collaboration of these two methods, improving the adaptability of the measurement system to different mine environments and making the measurement work more flexible and efficient.

[0205] Example 3

[0206] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain cases, it can also be a mobile phone, tablet computer, monitoring terminal, or other smart device, as well as an image acquisition device with processing capabilities. Figure 5 As shown, the electronic device may include:

[0207] Memory 510 storing executable program code;

[0208] Processor 520 coupled to memory 510;

[0209] The processor 520 calls the executable program code stored in the memory 510 to execute some or all of the steps in the collaborative positioning method in the mine topography measurement of Embodiment 1.

[0210] This invention discloses a computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps in the cooperative positioning method for mine topographic surveying in Embodiment 1.

[0211] This invention also discloses a computer program product, wherein when the computer program product is run on a computer, the computer performs some or all of the steps in the collaborative positioning method for mine topographic surveying in Embodiment 1.

[0212] This invention also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer performs some or all of the steps in the collaborative positioning method for mine topographic surveying in Embodiment 1.

[0213] In various embodiments of the present invention, it should be understood that the sequence number of each process does not necessarily 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.

[0214] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0215] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0216] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0217] In the embodiments provided by this invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0218] Those skilled in the art will understand that some or all of the steps in the various methods of the embodiments described can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0219] The above provides a detailed description of the collaborative positioning method, system, electronic device, and storage medium for mine topographic surveying disclosed in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method of cooperative positioning in mine topography surveying, characterized in that, The method comprises the following steps: Receiving satellite positioning signals obtained by the positioning module of the unmanned ship, and if it is detected that the current unmanned ship is in a satellite lock loss state, the next step is performed; Receiving monitoring data obtained by the unmanned aerial vehicle hovering above the mine pit, the monitoring data including positioning data detected by the positioning module and height information detected by the laser altimeter, wherein the height information is the height information of the unmanned aerial vehicle from the water surface; Sending corresponding ultra-wideband pulse signals to the ultra-wideband base station at the unmanned aerial vehicle hovering above the mine pit through the ultra-wideband tag arranged on the unmanned ship, calculating the relative position relationship between the corresponding unmanned aerial vehicle and the unmanned ship at the ultra-wideband base station according to the obtained ultra-wideband pulse signals, and sending the relative position relationship between the unmanned aerial vehicle and the unmanned ship, the positioning data detected by the positioning module, and the height information detected by the laser altimeter to the corresponding unmanned ship through the communication module; Determining the optimized positioning information of the corresponding unmanned ship according to the position relationship, the positioning data detected at the unmanned aerial vehicle, and the height information.

2. The method of collaborative positioning in mine terrain surveying of claim 1, wherein, After receiving the satellite positioning signals obtained by the positioning module of the unmanned ship, the method further comprises the following steps: Determining the satellite weight parameter according to the obtained number of visible satellites and position dilution of precision; Determining the ultra-wideband weight parameter according to the signal-to-noise ratio parameter and distance validity of the obtained ultra-wideband signal; Determining the inertial measurement weight parameter according to the obtained satellite availability and motion state information of the unmanned ship; Determining the position detection state of the unmanned ship according to the satellite weight parameter, the ultra-wideband weight parameter, and the inertial measurement weight parameter.

3. The method of collaborative positioning in mine terrain surveying of claim 2, wherein, The cooperative positioning method further comprises the following steps: Detecting the innovation value by chi-square test, and if the innovation value exceeds the threshold, reducing the satellite weight parameter; Detecting whether there is multipath interference of the ultra-wideband signal, and if so, dynamically reducing the ultra-wideband weight parameter; When the speed estimation value continuously falls below the threshold, forcibly entering the zero-speed correction mode.

4. The method of collaborative positioning in mine terrain surveying of claim 2, wherein, The cooperative positioning method further comprises the following steps: When the unmanned ship is not in the lock loss state, constructing the state vector feature according to the satellite original coordinates, and obtaining the initialized state vector and covariance matrix; Performing state prediction and covariance prediction according to the current position state, three-axis acceleration, and time interval to obtain corresponding prediction state information and prediction covariance matrix; wherein each sensor is clock-aligned through time stamping; Obtaining multi-source observation data, the multi-source observation data including satellite observation data, inertial navigation data, and ultra-wideband ranging data; Calculating the Kalman gain for each observation data to perform state updating to obtain optimized observation parameters, and outputting the optimized unmanned ship coordinates.

5. The method of collaborative positioning in mine terrain surveying of claim 1, wherein, Before receiving the monitoring data obtained by the unmanned aerial vehicle hovering above the mine pit, the method further comprises the following steps: Before cooperative positioning, using the unmanned aerial vehicle to perform aerial survey to obtain the mine pit orthophoto and the corresponding mine pit three-dimensional model, and determining the corresponding measurement route according to the mine pit orthophoto and the mine pit three-dimensional model, the measurement route including the measurement driving route and the hovering point of the unmanned aerial vehicle; The unmanned aerial vehicle and the unmanned ship measure the mine pit terrain according to the measured travel route, and the unmanned aerial vehicle hovers according to the hovering point as a signal base station.

6. The method of collaborative positioning in mine terrain surveying of claim 5, wherein, After the aerial survey is performed by using the unmanned aerial vehicle to obtain the mine pit orthographic image and the corresponding mine pit three-dimensional model, the method further comprises: According to the mine pit condition obtained by the aerial survey, a corresponding matching number of unmanned aerial vehicles is determined; if the mine pit condition matches the first condition, one unmanned aerial vehicle is used for subsequent terrain measurement; If the mine pit condition matches the second condition, at least three unmanned aerial vehicles are used for terrain measurement, and one of the three unmanned aerial vehicles is used as a main unmanned aerial vehicle, and the other two unmanned aerial vehicles are used as auxiliary unmanned aerial vehicles; wherein the main unmanned aerial vehicle hovers at a first height to provide a reference signal, and the auxiliary unmanned aerial vehicles hover at a second height to relay signals; the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicles communicate through ultra-wideband signals.

7. The method of collaborative positioning in mine terrain surveying of claim 5, wherein, The cooperative positioning method further comprises: The signal coverage range is expanded by arranging a relay rod at the high point; After the optimal positioning information of the corresponding unmanned ship is determined, the method further comprises: The unmanned ship performs fusion calculation on the obtained multi-source data to obtain three-dimensional coordinates of underwater points, and generates a digital elevation model of underwater terrain for data splicing with the ground model.

8. A cooperative positioning system in mine topography surveying, characterized by Comprise: A first receiving module is configured to receive satellite positioning signals obtained by a positioning module of the unmanned ship, and if it is detected that the current unmanned ship is in a satellite lock loss state, the next step is performed; A second receiving module is configured to receive monitoring data obtained by an unmanned aerial vehicle hovering above the mine pit, the monitoring data comprising positioning data detected by a positioning module and height information detected by a laser altimeter, wherein the height information is the height information of the unmanned aerial vehicle from the water surface; A ranging module is configured to send corresponding ultra-wideband pulse signals to an ultra-wideband base station at the unmanned aerial vehicle hovering above the mine pit through an ultra-wideband tag arranged on the unmanned ship, calculate the relative position relationship between the unmanned aerial vehicle and the unmanned ship at the ultra-wideband base station according to the obtained ultra-wideband pulse signals, and send the relative position relationship between the unmanned aerial vehicle and the unmanned ship, the positioning data detected by the positioning module, and the height information detected by the laser altimeter to the corresponding unmanned ship through a communication module. A positioning optimization module is configured to determine the optimal positioning information of the corresponding unmanned ship according to the position relationship, the positioning data detected by the unmanned aerial vehicle, and the height information.

9. An electronic device, comprising: Comprise: A memory storing executable program code; A processor coupled to the memory; The processor invokes the executable program code stored in the memory to execute the cooperative positioning method in the mine pit terrain measurement of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, wherein the computer program causes the computer to execute the cooperative positioning method in the mine pit terrain measurement of any one of claims 1 to 7.

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