Space coordinate processing method and device, computer equipment and storage medium

Abstract

The invention relates to a space coordinate processing method and device, computer equipment and a storage medium. The processing system of the space coordinates comprises an underwater node and a water surface buoy, and the processing method of the space coordinates comprises the following steps: acquiring a relative position between the underwater node and the water surface buoy; based on the relative position, obtaining the position coordinate of the underwater node; on the basis of the position coordinates and a preset spatial resolution, bitmap space representation is carried out on the underwater node to obtain compressed position information of the underwater node in a bitmap space, and the compressed position information comprises spatial position coordinate representation; and sending the compressed position information to a preset receiving terminal for resolving to obtain target position information of the underwater node. Therefore, the data transmission efficiency and the positioning precision in the low-bandwidth underwater acoustic channel can be improved.

Description

Technical Field

[0001] This application relates to the field of underwater positioning technology, and in particular to a method, apparatus, computer equipment, and storage medium for processing spatial coordinates. Background Technology

[0002] Underwater acoustic communication is currently the most important means of long-distance communication in underwater environments. In underwater positioning systems, traditional satellite-assisted positioning methods are widely used to provide position references and auxiliary positioning information.

[0003] Traditional satellite-assisted positioning methods typically rely on large underwater acoustic communication bandwidth and high communication rates to support high-frequency, high-capacity exchange of location information between nodes.

[0004] However, with limited bandwidth in underwater acoustic communication, the transmission of large amounts of raw location data can lead to communication congestion and delays, thereby affecting the positioning accuracy of the entire underwater positioning system. Summary of the Invention

[0005] This application provides a method, apparatus, computer device, and storage medium for processing spatial coordinates, aiming to solve the technical problem that the transmission of a large amount of raw location data can lead to communication congestion and delay when underwater acoustic communication bandwidth is limited, thereby affecting the positioning accuracy of the entire underwater positioning system.

[0006] In a first aspect, embodiments of this application provide a method for processing spatial coordinates. The spatial coordinate processing system includes underwater nodes and surface buoys. The spatial coordinate processing method includes:

[0007] Obtain the relative position between the underwater node and the surface buoy;

[0008] Based on the relative position, the position coordinates of the underwater node are obtained;

[0009] Based on the location coordinates and the preset spatial resolution, the underwater node is represented by a bitmap space to obtain the compressed location information of the underwater node in the bitmap space, wherein the compressed location information includes spatial location coordinates.

[0010] The compressed location information is sent to a preset receiving terminal for processing to obtain the target location information of the underwater node.

[0011] In some possible implementations, the underwater node includes a target underwater node and an underwater anchor point. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain compressed position information of the underwater node in bitmap space. The compressed position information includes spatial position coordinate representation, including:

[0012] Obtain the position coordinates of the underwater anchor point;

[0013] Based on the location coordinates of the underwater anchor point and the location coordinates of the target underwater node, the latitude, longitude and depth values ​​of the target underwater node are transformed to obtain the ENU coordinates of the target underwater node;

[0014] Based on the ENU coordinates, the preset ENU recovery coordination inverse operation operator, and the preset coordination operator in the bitmap space, the ENU coordinates of the target underwater node are transformed in the bitmap space to obtain the spatial position coordinate representation of the target underwater node in the bitmap space.

[0015] In some possible implementations, the bitmap space representation is a 0th-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0016] Based on the location coordinates and the preset 0th-order bitmap space resolution, the underwater node is represented by a 0th-order bitmap space to obtain the spatial location coordinates of the target underwater node in the 0th-order bitmap space.

[0017] In some possible implementations, the bitmap space representation is a first-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0018] Based on the location coordinates and the preset first-order bitmap space resolution, the underwater node is represented by a first-order bitmap space to obtain the spatial location coordinates of the target underwater node in the first-order bitmap space.

[0019] In some possible implementations, the bitmap space representation is a high-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0020] Based on the location coordinates and the preset high-order bitmap spatial resolution, the underwater node is represented by a high-order bitmap space to obtain the spatial location coordinates of the target underwater node in the high-order bitmap space.

[0021] In some possible implementations, the method includes:

[0022] Retrieve the one-dimensional data structure, binary position index, and bit length in the bitmap space;

[0023] Based on the one-dimensional data structure, the binary position index, and the bit length, the preset first-order bitmap spatial resolution is obtained.

[0024] In some possible implementations, obtaining the relative position between the underwater node and the surface buoy, and obtaining the position coordinates of the underwater node based on the relative position, includes:

[0025] The relative position between the underwater node and the surface buoy is obtained using triangulation or hyperbolic positioning methods; based on the relative position, the position coordinates of the underwater node are obtained.

[0026] Secondly, embodiments of this application also provide a spatial coordinate processing apparatus, which includes a unit for performing the above-described method.

[0027] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0028] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0029] This application provides a method, apparatus, computer device, and storage medium for processing spatial coordinates. The method includes: acquiring the relative position between an underwater node and a surface buoy; obtaining the position coordinates of the underwater node based on the relative position; performing bitmap spatial representation on the underwater node based on the position coordinates and a preset spatial resolution to obtain compressed position information of the underwater node in the bitmap space, wherein the compressed position information includes spatial position coordinate representation; and sending the compressed position information to a preset receiving terminal for calculation to obtain target position information of the underwater node.

[0030] The embodiments provided in this application introduce a bitmap spatial representation mechanism to compress the original high-precision floating-point position coordinates into a compact multi-dimensional bitmap sequence. This achieves efficient position information compression without relying on traditional compression algorithms, reducing the amount of data required for underwater acoustic communication and lowering the communication load. The compressed bitmap sequence can be transmitted within a single underwater acoustic communication frame, avoiding communication conflicts and packet loss caused by high-frequency, large-volume transmission, thereby improving data transmission efficiency and the system's positioning accuracy in low-bandwidth underwater acoustic channels.

[0031] Furthermore, by incorporating preset spatial resolution parameters during the compression process, a flexible balance can be achieved between compression rate and positioning accuracy, ensuring that the compressed position information still has sufficient spatial resolution to meet the accuracy requirements of underwater positioning systems. Attached Figure Description

[0032] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0033] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0035] Figure 1 A flowchart illustrating a spatial coordinate processing method provided in an embodiment of this application;

[0036] Figure 2 This is a schematic diagram of the ordered spatial partitioning representation provided in the embodiments of this application;

[0037] Figure 3 This is a schematic diagram illustrating the interaction between AUV and USV in a spatial coordinate processing device provided in an embodiment of this application.

[0038] Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0040] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0041] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0042] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0043] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0044] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0045] Underwater acoustic communication is currently the most important means of long-distance communication in underwater environments. In underwater positioning systems, traditional satellite-assisted positioning methods are widely used to provide position references and auxiliary positioning information.

[0046] Traditional satellite-assisted positioning methods typically rely on large underwater acoustic communication bandwidth and high communication rates to support high-frequency, high-capacity exchange of location information between nodes.

[0047] However, with limited bandwidth in underwater acoustic communication, the transmission of large amounts of raw location data can lead to communication congestion and delays, thereby affecting the positioning accuracy of the entire underwater positioning system.

[0048] To address the technical problem that the transmission of large amounts of raw location data can lead to communication congestion and delays due to limited underwater acoustic communication bandwidth, thereby affecting the positioning accuracy of the entire underwater positioning system, this application provides a spatial coordinate processing method that can improve the positioning accuracy of the underwater positioning system.

[0049] See Figure 1 , Figure 1 This is a flowchart illustrating a spatial coordinate processing method provided in an embodiment of this application. The spatial coordinate processing system includes underwater nodes and surface buoys, and the spatial coordinate processing method includes:

[0050] Step 110: Obtain the relative position between the underwater node and the surface buoy.

[0051] Step 120: Based on the relative position, obtain the position coordinates of the underwater node.

[0052] Step 130: Based on the location coordinates and the preset spatial resolution, perform bitmap spatial representation on the underwater node to obtain the compressed position information of the underwater node in the bitmap space.

[0053] The compressed location information includes spatial location coordinates.

[0054] Step 140: Send the compressed location information to a preset receiving terminal for calculation to obtain the target location information of the underwater node.

[0055] This embodiment introduces a bitmap spatial representation mechanism to compress the original high-precision floating-point position coordinates into a compact multi-dimensional bitmap sequence. It achieves efficient position information compression without relying on traditional compression algorithms, reducing the amount of data required for underwater acoustic communication and lowering the communication load. This allows the compressed bitmap sequence to be transmitted within a single underwater acoustic communication frame, avoiding communication conflicts and packet loss caused by high-frequency, large-volume transmission, thereby improving data transmission efficiency and the system's positioning accuracy in low-bandwidth underwater acoustic channels.

[0056] Furthermore, by incorporating preset spatial resolution parameters during the compression process, a flexible balance can be achieved between compression rate and positioning accuracy, ensuring that the compressed position information still has sufficient spatial resolution to meet the accuracy requirements of underwater positioning systems.

[0057] Furthermore, the compressed location information is small in size and transmits quickly, enabling underwater nodes to update their own locations and synchronize network topology information more frequently, thereby better supporting the dynamic deployment and adaptive control of underwater unmanned cooperative networks.

[0058] In some possible implementations, obtaining the relative position between the underwater node and the surface buoy, and obtaining the position coordinates of the underwater node based on the relative position, includes:

[0059] The relative position between the underwater node and the surface buoy is obtained using triangulation or hyperbolic positioning methods; based on the relative position, the position coordinates of the underwater node are obtained.

[0060] For example, multiple satellite-positioned surface buoys (with known precise coordinates) can be deployed on the water surface. The surface buoys communicate with underwater nodes via underwater acoustic signals (such as ultrasound) to measure distance or time difference of arrival (TDOA). The position of the underwater node can be calculated by using geometric relationships (such as triangulation) and combining the coordinates of the surface buoys.

[0061] Specifically, the satellite-assisted positioning method for surface buoys may include the following steps:

[0062] 1. Deployment and coordinate calibration of surface buoys

[0063] Select a surface buoy with satellite positioning capabilities (built-in GPS / BeiDou module) and equip it with an underwater acoustic transducer (for transmitting / receiving ultrasonic signals).

[0064] Among them, the surface buoys must be able to withstand wind and waves to ensure stable operation on the water surface.

[0065] Deploy surface buoys to the target sea area and, once stabilized, obtain precise coordinates (X1, Y1, Z1), (X2, Y2, Z2), (X3, Y3, Z3)... using a satellite positioning module (deploy at least 3 surface buoys to form a positioning network). Record the three-dimensional coordinates of each surface buoy as reference points for subsequent positioning.

[0066] 2. Interaction of distance measurement between underwater nodes and surface buoys

[0067] Underwater equipment (such as AUVs and ROVs) transmits underwater acoustic signals (ultrasonic pulses) to surrounding surface buoys according to preset programs or real-time commands. The signals may contain target identification, communication timestamps, and other information for buoy identification and distance measurement. Upon receiving the underwater acoustic signal, the surface buoy records the time of arrival (TOA) or the time difference of arrival (TDOA) between different surface buoys.

[0068] TOA-based ranging: Given the speed of sound in water, v (approximately 1500 m / s), the distance r between the target and the surface buoy i is... i = v × (signal reception time - signal transmission time).

[0069] Ranging based on TDOA: The time difference Δt between the measurement signal arriving at buoy i and buoy j is combined with the known distance d between the two buoys. ij The position of the underwater node is calculated using the hyperbolic positioning principle (requiring at least 3 surface buoys).

[0070] 3. Calculate the position coordinates of the underwater nodes using geometric relationships.

[0071] 3-1. Triangulation Method (TOA Scenario)

[0072] Assume the underwater node coordinates are (X,Y,Z), and the surface buoy i's coordinates are (X,Y,Z). i ,Y i Z i The measured distance is r. i Then the equation is satisfied:

[0073]

[0074] Solve the equations of at least three surface buoys simultaneously, and solve for the coordinates (X, Y, Z) of the underwater node using geometric methods (such as the least squares method).

[0075] 3-2. Hyperbolic Positioning Method (TDOA Scenario)

[0076] For surface buoys i and j, the time difference Δt corresponds to the distance difference Δr = v × Δt, and the position of the underwater node satisfies the hyperbolic equation:

[0077]

[0078] Solve the hyperbolic equations of at least three pairs of surface buoys simultaneously, and the intersection point is the location of the underwater node (where the Z coordinate needs to be calculated with the help of a depth sensor).

[0079] 4. Error Correction

[0080] 4-1 Sound speed correction

[0081] Since water temperature, salinity, and depth affect the speed of sound v (e.g., the speed of sound in the deep sea is about 1540 m / s, while in shallow sea it may fluctuate due to temperature changes), it is necessary to measure the real-time speed of sound using a sound velocity profiler or to incorporate a sound velocity compensation algorithm into a surface buoy.

[0082] 4-2 Dynamic calibration of surface buoy position

[0083] Since ocean waves and currents can cause surface buoys to drift, it is necessary to update their coordinates regularly via satellite positioning (e.g., once per minute) or add mutual ranging functionality (e.g., USBL) between surface buoys to correct positional deviations in real time.

[0084] 4-3. Multi-data fusion

[0085] By combining inertial navigation (IMU) data, the positioning results are smoothed to reduce position jumps caused by underwater acoustic signal noise (such as multipath effects).

[0086] In some possible implementations, the underwater node includes a target underwater node and an underwater anchor point. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain compressed position information of the underwater node in bitmap space. The compressed position information includes spatial position coordinate representation, including:

[0087] Step 21: Obtain the position coordinates of the underwater anchor point.

[0088] Step 22: Based on the position coordinates of the underwater anchor point and the position coordinates of the target underwater node, transform the latitude, longitude and depth values ​​of the target underwater node to obtain the ENU coordinates of the target underwater node.

[0089] Step 23: Based on the ENU coordinates, the preset ENU recovery coordination inverse operation operator, and the preset coordination operator in the bitmap space, perform a bitmap space transformation on the ENU coordinates of the target underwater node to obtain the spatial position coordinate representation of the target underwater node in the bitmap space.

[0090] In some possible implementations, the bitmap space representation is a 0th-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0091] Based on the location coordinates and the preset 0th-order bitmap space resolution, the underwater node is represented by a 0th-order bitmap space to obtain the spatial location coordinates of the target underwater node in the 0th-order bitmap space.

[0092] For example, the spatial resolution of a 0th-order bitmap space can be calculated using the following formula.

[0093]

[0094] Among them, R i The spatial resolution of the 0th-order bitmap space. Let LB be the bit length, and posbinary be the binary position index of the node in the bitmap space. i For example, B is a single-dimensional data structure in bitmap space. i = (0, sign, posbinary).

[0095] Specifically, the 0th-order bitmap space representation may include the following process:

[0096] 1) Define the underwater node P = (x, y, z) in ENU as follows: Let B be the representation in a 0th-order bitmap space, and let B(·) be the operator for computational coordination in the bitmap space. -1 (·) is the inverse operation for restoring coordination in ENU, and can be represented as:

[0097] 2) Determine the coordinates of the underwater anchor point P0;

[0098] 3) Target underwater node P i T r Transformation can be achieved using formulas.

[0099] 3-1) P i The latitude, longitude, and depth values ​​can be transformed into ENU coordinates using the following formula: ENUP Ri =P i -P0.

[0100] 3-2) Calculate P i The spatial coordinate representation of a position in a 0th-order bitmap space is given by the following formula:

[0101]

[0102] 4) Send the location information of the target underwater node in the first-order bitmap space to the preset receiving terminal;

[0103] 5) Preset receiving terminal calculation Target location information.

[0104] Among them, the target underwater node P i The following formula can be used:

[0105]

[0106] In some possible implementations, the bitmap space representation is a first-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0107] Based on the location coordinates and the preset first-order bitmap space resolution, the underwater node is represented by a first-order bitmap space to obtain the spatial location coordinates of the target underwater node in the first-order bitmap space.

[0108] In some possible implementations, the preset first-order bitmap spatial resolution can be calculated in the following manner:

[0109] Step 31: Obtain the one-dimensional data structure, binary position index, and bit length in the bitmap space.

[0110] Step 32: Based on the one-dimensional data structure, the binary position index, and the bit length, obtain the preset first-order bitmap spatial resolution.

[0111] For example, for a first-order bitmap representation, the spatial resolution of the first-order bitmap can be calculated using the following formula:

[0112]

[0113] Among them, R i Given a first-order bitmap space resolution, the one-dimensional data structure in the first-order bitmap space is: in, For binary position indexes in a first-order bitmap space, The length is LB.

[0114] Specifically, the first-order bitmap space representation may include the following process:

[0115] 1) Define the representation of the underwater node P = (x, y, z) in ENU. Let B(·) be the representation in a first-order bitmap space, and let B(·) be the operator for computational coordination in the bitmap space. -1 (·) is the inverse operation for restoring coordination in ENU, and can be represented as:

[0116] 2) Determine the coordinates of the underwater anchor point P0;

[0117] 3) Target underwater node P i T r Transformation can be achieved using formulas.

[0118] 3-1) P i The latitude, longitude, and depth values ​​can be transformed into ENU coordinates using the following formula: ENUP Ri =P i -P0.

[0119] 3-2) Calculate P i For the spatial coordinate representation of a position in a first-order bitmap space, please refer to the following formula:

[0120]

[0121] 4) Send the location information of the target underwater node in the first-order bitmap space to the preset receiving terminal;

[0122] 5) Preset receiving terminal calculation

[0123] Among them, the target underwater node P i The following formula can be used:

[0124]

[0125] In some possible implementations, the bitmap space representation is a high-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including:

[0126] Based on the location coordinates and the preset high-order bitmap spatial resolution, the underwater node is represented by a high-order bitmap space to obtain the spatial location coordinates of the target underwater node in the high-order bitmap space.

[0127] See Figure 2 , Figure 2 This is a schematic diagram of the spatial partitioning representation of a high-order data structure provided in an embodiment of this application.

[0128] See Figure 2 For higher-order bitmap space representations, suppose the nth node... th The one-dimensional bitmap mapping data structure is as follows nth th The order is represented as

[0129] Px can then be calculated using the following formula:

[0130]

[0131] Py can then be calculated using the following formula:

[0132]

[0133] Pz can then be calculated using the following formula:

[0134]

[0135] Specifically, high-order bitmap space representation may include the following process:

[0136] 1) Define the representation of the underwater node P = (x, y, z) in ENU. Let B(·) be the representation in a first-order bitmap space, and let B(·) be the operator for computational coordination in the bitmap space. -1 (·) is the inverse operation for restoring coordination in ENU, and can be represented as:

[0137] 2) Determine the coordinates of the underwater anchor point P0;

[0138] 3) Target underwater node P i T r Transformation.

[0139] 3-1) P i The latitude, longitude, and depth values ​​can be transformed into ENU coordinates using the following formula: ENUP Ri =P i -P0.

[0140] 3-2) Calculate P i For the spatial coordinate representation of a position in a first-order bitmap space, please refer to the following formula:

[0141]

[0142] 4) Send the location information of the target underwater node in the first-order bitmap space to the preset receiving terminal;

[0143] 5) Preset receiving terminal calculation

[0144] Among them, the target underwater node P i The following formula can be used:

[0145]

[0146] See Figure 3 , Figure 3 This is a schematic diagram illustrating the interaction between AUV and USV in a spatial coordinate processing device provided in an embodiment of this application.

[0147] like Figure 3 As shown, surface buoys, such as unmanned surface vehicles (USVs), obtain their actual location information based on satellite positioning. Then, underwater acoustic positioning technology is used to obtain the relative positional relationship between underwater nodes, such as autonomous underwater vehicles (AUVs) and the USV. The spatial position is then converted into a multi-dimensional bitmap sequence according to the algorithm described above and sent to the corresponding node (i.e., the preset receiving terminal) for processing.

[0148] Therefore, this application adopts a real-time high-precision spatial coordinate reference algorithm based on satellite positioning and attitude measurement, and uses a low-overhead data structure to represent the node positions in the acoustic communication network tailored for underwater unmanned collaborative networks in the Wi-Fi network architecture. This data structure is designed by converting spatial positions into multi-dimensional bitmap sequences through spatial bitmap mapping, thereby achieving dimensionality reduction of node position information. In this way, while maintaining extremely high spatial resolution, a position information compression effect of up to 8 times can be achieved without the use of compression algorithms. Furthermore, while ensuring accurate data transmission, communication overhead is reduced, solving the problems of narrow bandwidth and low communication rate in underwater acoustic communication systems.

[0149] Furthermore, this data structure enables precise synchronization of network location information with minimal network overhead, providing effective data support for the dynamic deployment and adaptive control of underwater acoustic communication networks.

[0150] Corresponding to the above-described spatial coordinate processing method, this application also provides a spatial coordinate processing apparatus. This spatial coordinate processing apparatus includes a unit for executing the above-described spatial coordinate processing method, and can be configured in a desktop computer, tablet computer, laptop computer, or other terminal.

[0151] like Figure 4 As shown in the figure, this application provides a computer device including a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0152] Memory 113 is used to store computer programs;

[0153] In one embodiment of this application, when the processor 111 executes the program stored in the memory 113, it implements the spatial coordinate processing method provided in any of the foregoing method embodiments, including:

[0154] Obtain the relative position between the underwater node and the surface buoy;

[0155] Based on the relative position, the position coordinates of the underwater node are obtained;

[0156] Based on the location coordinates and the preset spatial resolution, the underwater node is represented by a bitmap space to obtain the compressed location information of the underwater node in the bitmap space, wherein the compressed location information includes spatial location coordinates.

[0157] The compressed location information is sent to a preset receiving terminal for processing to obtain the target location information of the underwater node.

[0158] It will be understood by those skilled in the art 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 computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0159] Therefore, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, it implements the steps of the spatial coordinate processing method provided in any of the foregoing method embodiments, including:

[0160] Obtain the relative position between the underwater node and the surface buoy;

[0161] Based on the relative position, the position coordinates of the underwater node are obtained;

[0162] Based on the location coordinates and the preset spatial resolution, the underwater node is represented by a bitmap space to obtain the compressed location information of the underwater node in the bitmap space, wherein the compressed location information includes spatial location coordinates.

[0163] The compressed location information is sent to a preset receiving terminal for processing to obtain the target location information of the underwater node.

[0164] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0165] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0166] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0167] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application 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.

[0168] 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 storage medium. Based on this understanding, the technical solution of this application, 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 storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0169] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0170] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0171] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for processing spatial coordinates, characterized in that, The spatial coordinate processing system includes underwater nodes and surface buoys, and the spatial coordinate processing method includes: Obtain the relative position between the underwater node and the surface buoy; Based on the relative position, the position coordinates of the underwater node are obtained; Based on the location coordinates and the preset spatial resolution, the underwater node is represented by a bitmap space to obtain the compressed location information of the underwater node in the bitmap space, wherein the compressed location information includes spatial location coordinates. The compressed location information is sent to a preset receiving terminal for processing to obtain the target location information of the underwater node.

2. The method according to claim 1, characterized in that, The underwater node includes a target underwater node and an underwater anchor point. Based on the position coordinates and a preset spatial resolution, the underwater node is represented by a bitmap space to obtain compressed position information of the underwater node in the bitmap space. The compressed position information includes spatial position coordinate representation, including: Obtain the position coordinates of the underwater anchor point; Based on the location coordinates of the underwater anchor point and the location coordinates of the target underwater node, the latitude, longitude and depth values ​​of the target underwater node are transformed to obtain the ENU coordinates of the target underwater node; Based on the ENU coordinates, the preset ENU recovery coordination inverse operation operator, and the preset coordination operator in the bitmap space, the ENU coordinates of the target underwater node are transformed in the bitmap space to obtain the spatial position coordinate representation of the target underwater node in the bitmap space.

3. The method according to claim 1, characterized in that, The bitmap space representation is a 0th-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including: Based on the location coordinates and the preset 0th-order bitmap space resolution, the underwater node is represented by a 0th-order bitmap space to obtain the spatial location coordinates of the target underwater node in the 0th-order bitmap space.

4. The method according to claim 1, characterized in that, The bitmap space representation is a first-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including: Based on the location coordinates and the preset first-order bitmap space resolution, the underwater node is represented by a first-order bitmap space to obtain the spatial location coordinates of the target underwater node in the first-order bitmap space.

5. The method according to claim 1, characterized in that, The bitmap space representation is a high-order bitmap space representation. Based on the position coordinates and a preset spatial resolution, the underwater node is represented in bitmap space to obtain the spatial position coordinates of the target underwater node in the bitmap space, including: Based on the location coordinates and the preset high-order bitmap spatial resolution, the underwater node is represented by a high-order bitmap space to obtain the spatial location coordinates of the target underwater node in the high-order bitmap space.

6. The method according to claim 4, characterized in that, The method includes: Retrieve the one-dimensional data structure, binary position index, and bit length in the bitmap space; Based on the one-dimensional data structure, the binary position index, and the bit length, the preset first-order bitmap spatial resolution is obtained.

7. The method according to claim 1, characterized in that, The step of obtaining the relative position between the underwater node and the surface buoy, and obtaining the position coordinates of the underwater node based on the relative position, includes: The relative position between the underwater node and the surface buoy is obtained using triangulation or hyperbolic positioning methods; based on the relative position, the position coordinates of the underwater node are obtained.

8. A spatial coordinate processing device, characterized in that, Includes a unit for performing the method as described in any one of claims 1-7.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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