Data processing method and related device

Abstract

The invention provides a data processing method and a related device. In the data processing method provided by the application, perception data acquired by UE is divided into first target data and second target data, an object corresponding to the first target data has a corresponding projection in a reconstruction space, and an object corresponding to the second target data does not have a corresponding projection in the reconstruction space. The first target data and the second target data are compressed in different compression modes and uploaded to the base station, and the compression degree corresponding to the first target data is higher than that corresponding to the second target data, so that the data volume interacted with the base station is reduced, the communication efficiency in the environment reconstruction process is improved, and the bandwidth load is reduced.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a data processing method and related devices. Background Art

[0002] With the rapid development of wireless communication technology, base stations can restore information about the surrounding environment of user equipment (UE) based on the perception data uploaded by UE to achieve environmental reconstruction. In the process of real-time maintenance and reconstruction of the map, the base station needs to obtain a large amount of perception data to ensure the performance of environmental reconstruction. However, the upload efficiency of UE is not high when bandwidth is limited. How to improve the communication efficiency of the environmental reconstruction process has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present application provides a data processing method and related devices, aiming to improve communication efficiency and reduce bandwidth load during environment reconstruction.

[0004] In a first aspect, the present application provides a data processing method, which is applied to a terminal device, and the method includes: obtaining target perception data, the target perception data is the perception data of a target object in a first space where the terminal device is located; using a first compression method to compress first target data in the target perception data to obtain first compressed data, the first target data is the perception data of a first target object in the first space, and a reconstruction space corresponding to the first space contains a first reconstructed object corresponding to the first target object; sending the first compressed data and first index information to a network device, the first index information being used to indicate that the first compressed data corresponds to the first reconstructed object.

[0005] In this method, first target data is determined from target perception data based on the reconstructed objects already existing in the reconstructed space corresponding to the first space. Compressing the first target data using a first compression processing method can reduce the amount of data required to update the first reconstructed object, thereby reducing the amount of data interacting with the base station, improving communication efficiency during the environment reconstruction process, and reducing bandwidth load.

[0006] At the same time, because the base station uses the correlation between the first target data and the data corresponding to the first reconstructed object when updating the reconstructed map, objects in the UE's perception blind area can be retained in the reconstructed map, thereby improving the accuracy of the reconstructed map.

[0007] In some implementations, before compressing the first target data in the target perception data using the first compression method to obtain the first compressed data, the method further includes:

[0008] Receive first indication information from a network device, where the first indication information is used to determine first target data; determine the first target data from target perception data based on the first indication information, and obtain first index information based on the first indication information.

[0009] In some implementations, the method further includes:

[0010] Use a second compression method to compress the second target data in the target perception data to obtain second compressed data, where the second target data is the perception data of the second target object in the first space, and the reconstructed space does not include a second reconstructed object corresponding to the second target object; send the second compressed data to the network device.

[0011] In some implementations, the first compression method includes: determining posture data corresponding to the first target data as first compressed data, the posture data including position data and / or posture data.

[0012] In some implementations, the first compression method includes: determining the difference between the pose data corresponding to the first target data and the first pose data as the first compressed data, the pose data includes position data and / or posture data, and the first pose data is the pose data of the first reconstructed object in the reconstructed space.

[0013] In some implementations, the position data includes geometric center point data and / or geometric vertex data, and the attitude data includes yaw angle data.

[0014] Determining the position and posture data of the first target object as the first compressed data can minimize the amount of data required to update the first reconstructed object while ensuring reconstruction performance, thereby improving communication efficiency.

[0015] In some implementations, the first indication information includes at least one target data, and the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstruction space. Each target data in the at least one target data includes posture data of the corresponding reconstructed object, and the posture data includes position data and / or posture data.

[0016] Determining first target data from the target perception data according to the first indication information includes:

[0017] Acquire posture data corresponding to each target data in the target perception data, wherein a difference between a posture indicated by posture data corresponding to the first target data and a posture indicated by posture data in a third target data in at least one target data is less than a posture difference threshold, and / or a distance between position data corresponding to the first target data and position data in the third target data is less than a first distance threshold, and the third target data corresponds to the first reconstructed object.

[0018] In some implementations, the third target data further includes sampling point data of the first reconstructed object, where the sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on the first reconstructed object.

[0019] Wherein, the method further comprises:

[0020] Determine a first neighbor distance between the first reconstructed object and the first target object according to the sampling point data included in the third target data, where the first neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object;

[0021] Use the third compression method to compress the fourth target data to obtain third compressed data, the fourth target data is perception data of a fourth target object in the first target object, the first neighbor distance corresponding to the fourth target object is greater than or equal to the second threshold, and the compression ratio of the third compression method is higher than that of the second compression method; send the third compressed data to the network device.

[0022] The sampling point data of the reconstructed object sent by the base station is used as auxiliary information, and the first target data is further subdivided and compressed, so as to further improve the accuracy of the reconstructed map while ensuring communication efficiency, and meet the reconstruction performance requirements in different scenarios.

[0023] In some implementations, the first compressed data and the second compressed data are sent first, and the third compressed data is sent in an incremental layer.

[0024] When the number of uplink resources is limited, the requirement for uplink resources can be reduced through layered transmission.

[0025] In some implementations, the sampling point data of the first reconstructed object is used to indicate the position data of each point of at least one point on the first reconstructed object, including:

[0026] The sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on a first outer surface of the first reconstructed object, where the first outer surface includes at least one outer surface on the first reconstructed object.

[0027] The first nearest neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object, including:

[0028] The first neighbor distance is used to indicate the shortest distance between a first outer surface on the first target object and a second outer surface on the first reconstructed object, where the second outer surface is an outer surface on the first reconstructed object corresponding to the first outer surface on the first target object.

[0029] The first target object is further subdivided in units of faces, so that compressed data can be sent at a finer granularity, thereby improving reconstruction performance.

[0030] In some implementations, before receiving the first indication information from the network device, the method further includes:

[0031] First request information is sent to the network device, where the first request information is used to request sampling point data of the reconstructed object contained in the reconstructed space; wherein each target data contains the sampling point data of the corresponding reconstructed object.

[0032] The terminal device actively requests the sampling point data of the reconstructed object from the network device in response to the reconstruction performance requirements of different tasks, which can balance the requirements for reconstruction performance and communication efficiency for different scenarios.

[0033] In some implementations, the first indication information is also used to indicate a second distance threshold.

[0034] In some implementations, before compressing the first target data in the target perception data using the first compression method to obtain the first compressed data, the method further includes:

[0035] Sending posture data corresponding to each target data in multiple target data in target perception data to a network device, where the multiple target data correspond one-to-one to multiple target objects in a first space; receiving first indication information from the network device, where the first indication information is used to indicate the first target data and the second target data in the multiple target data.

[0036] In some implementations, the first indication information is further used to instruct that the first target data be compressed using a first compression method, and the first indication information is further used to instruct that the second target data be compressed using a second compression method.

[0037] In some implementations, before receiving the first indication information from the network device, the method further includes:

[0038] Sending second request information to the network device, where the second request information is used to request the sampling point data of the first reconstructed object.

[0039] In some implementations, the first compression method includes: determining residual coding data of the first target data and posture data corresponding to the first target data as first compressed data, and the posture data includes position data and / or posture data.

[0040] In a single UE timing scenario, the first target data and the second target data in the target perception data can be determined through the local historical data saved by the UE, so that different compression methods can be used to improve the communication efficiency between the UE and the base station, expanding the scenarios in which environmental reconstruction can be applied.

[0041] In some implementations, the method further includes:

[0042] Send third indication information to the network device, the third indication information is used to indicate compression processing of the first target data using the first compression method and compression processing of the second target data using the second compression method, and the third indication information is also used to indicate compression parameters of the first compression method and compression parameters of the second compression method.

[0043] In a second aspect, the present application provides a data processing method, applied to a network device, the method comprising:

[0044] Receive first compressed data from a terminal device, where the first compressed data is data obtained by processing first target data in a first compression method, the first target data is perception data of a first target object in a first space, and a reconstruction space corresponding to the first space contains a first reconstructed object corresponding to the first target object; update the reconstruction space according to the first compressed data.

[0045] In some implementations, the method further includes:

[0046] Receive second compressed data from the terminal device, where the second compressed data is data obtained by a second compression process on the second target data, the second target data is perception data of the second target object in the first space, and the reconstructed space does not contain a second reconstructed object corresponding to the second target object; update the reconstructed space according to the second compressed data.

[0047] In some implementations, the first compression method includes: determining posture data corresponding to the first target data as first compressed data, the posture data including position data and / or posture data.

[0048] In some implementations, updating the reconstruction space according to the first compressed data includes:

[0049] According to the difference between the pose data corresponding to the first target data and the first pose data, the position data of each point on the first reconstructed object in the reconstructed space is updated, and the first pose data is the pose data of the first reconstructed object.

[0050] In some implementations, before receiving the first compressed data from the terminal device, the method further includes:

[0051] Send first indication information to the terminal device, where the first indication information is used to determine first target data.

[0052] In some implementations, the first indication information includes at least one target data, and the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstruction space. Each target data in the at least one target data includes posture data of the corresponding reconstructed object, and the posture data includes position data and / or posture data.

[0053] In some implementations, the third target data in the at least one target data also includes sampling point data of the first reconstructed object, the sampling point data of the first reconstructed object is used to indicate the position data of each point in the at least one point on the first reconstructed object, and the third target data corresponds to the first reconstructed object.

[0054] The method also includes:

[0055] Receive third compressed data from the terminal device, the third compressed data is data obtained by processing the fourth target data by a third compression method, the fourth target data is perception data of a fourth target object in the first target object, the first neighbor distance corresponding to the fourth target object is greater than or equal to a second threshold, and the compression ratio of the third compression method is higher than that of the second compression method.

[0056] In some implementations, the sampling point data of the first reconstructed object is used to indicate the position data of each point of at least one point on the first reconstructed object, including:

[0057] The sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on a first outer surface of the first reconstructed object, where the first outer surface includes at least one outer surface on the first reconstructed object.

[0058] The first nearest neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object, including:

[0059] The first neighbor distance is used to indicate the shortest distance between a first outer surface on the first target object and a second outer surface on the first reconstructed object, where the second outer surface is an outer surface on the first reconstructed object corresponding to the first outer surface on the first target object.

[0060] In some implementations, sending the first indication information to the terminal device includes:

[0061] Receive posture data corresponding to each target data in multiple target data in target perception data of a terminal device, where the multiple target data correspond one-to-one to multiple target objects in a first space; determine first target data and second target data from the multiple target data, where the difference between the posture indicated by the posture data corresponding to the first target data and the posture indicated by the posture data in the third target data in at least one target data is less than a posture difference threshold, and / or, the distance between the position data corresponding to the first target data and the position data in the third target data is less than a first distance threshold, and the third target data corresponds to the first reconstructed object; send first indication information to the terminal device, where the first indication information is used to indicate the first target data and the second target data among the multiple target data.

[0062] In some implementations, the first indication information is further used to instruct that the first target data be compressed using a first compression method, and the first indication information is further used to instruct that the second target data be compressed using a second compression method.

[0063] In some implementations, the first compression method includes: determining residual coding data of the first target data and posture data corresponding to the first target data as first compressed data, and the posture data includes position data and / or posture data.

[0064] In a third aspect, the present application provides a data processing device, which includes various functional modules for implementing any of the data processing methods mentioned in the above implementations. Optionally, each module can be implemented by software and / or hardware.

[0065] In a fourth aspect, the present application provides a data processing device, including a processor, the processor is coupled to a memory, and can be used to execute instructions in the memory to implement the method in any possible implementation of the first aspect or the second aspect. Optionally, the device also includes a memory. Optionally, the device also includes a communication interface, and the processor is coupled to the communication interface.

[0066] In a fifth aspect, the present application provides a computer-readable medium storing a program code for execution by a device, wherein the program code includes a method for executing the method in the first aspect, the second aspect, or any possible implementation manner therein.

[0067] In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method in the first aspect, the second aspect, or any possible implementation manner thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0069] Figure 1 A schematic diagram of the architecture of a communication system used in an embodiment of the present application;

[0070] Figure 2 A flowchart of a data processing method provided by an embodiment of the present application;

[0071] Figure 3 A schematic diagram of rotating a data point provided by an embodiment of the present application;

[0072] Figure 4 A flowchart of a data processing method provided by an embodiment of the present application;

[0073] Figure 5 A flowchart of a data processing method provided by an embodiment of the present application;

[0074] Figure 6 A flowchart of a data processing method provided by an embodiment of the present application;

[0075] Figure 7 A simulation schematic diagram of a data processing method provided by an embodiment of the present application;

[0076] Figure 8 A schematic diagram of a simulation comparison between a data processing method provided by an embodiment of the present application and an existing data processing method;

[0077] Fig. 9 A schematic diagram of a simulation comparison between a data processing method provided by an embodiment of the present application and an existing data processing method;

[0078] Fig.10 A schematic diagram of the structure of a data processing device provided in one embodiment of the present application;

[0079] Fig.11 A schematic diagram of the structure of a data processing device provided in another embodiment of the present application;

[0080] Fig.12 A schematic diagram of the structure of a data processing device provided in yet another embodiment of the present application.

[0081] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0082] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0083] With the development of wireless communication technology, its application scenarios have expanded to areas such as autonomous driving, virtual reality (VR), and augmented reality (AR). In the above fields, wireless communication technology can be used to realize various data applications such as perception, imaging, and environmental reconstruction. For example, in environmental reconstruction, multiple UEs can perceive or observe the same environment from different viewing angles and send the perception data to network devices. The network devices can obtain a complete environmental map based on the fusion of perception data to achieve more detailed environmental reconstruction.

[0084] Figure 1 FIG. 1 is a schematic diagram of the architecture of a communication system used in an embodiment of the present application. Figure 1 As shown, the communication system includes a first communication device and a second communication device, wherein the first communication device can be Figure 1 The mobile phone 110, printer 120, and vehicle 130 in the embodiment may be other sensing devices in actual application. Figure 1 Only mobile phones, printers and vehicles are used as examples for explanation.

[0085] The perception device involved in the embodiments of the present application, which can also be referred to as a terminal, is an entity on the user side for receiving or transmitting signals, and is used to send uplink signals to network devices, or receive downlink signals from network devices. It includes devices that provide voice and / or data connectivity to users, for example, it may include a handheld device with a wireless connection function, or a processing device connected to a wireless modem. The perception device can communicate with the core network via a wireless access network (RAN) device, and exchange voice and / or data with the RAN. The terminal device may include user equipment, vehicle wireless communication technology (vehicle to x, V2X) terminal equipment, wireless terminal equipment, mobile terminal equipment, Internet of Things (IoT) terminal equipment, subscriber unit (subscriber unit), subscriber station (subscriber station), mobile station (mobile station), remote station (remote station), access point (access point, AP), remote terminal (remote terminal), access terminal (access terminal), user terminal (user terminal), user agent (user agent), or user equipment (user device), wearable device, vehicle-mounted equipment, drone, small base station, etc.

[0086] The second communication device is a network device 140, which can also be a terminal device with strong data processing capabilities. The network device 140 is a RAN device deployed in a wireless access network to provide wireless communication functions for terminal devices. In the embodiment of the present application, the RAN device can be a device that provides wireless communication function services, usually located on the network side, including but not limited to: the next generation base station (gNodeB, gNB) in the fifth generation (5th generation, 5G) communication system, the next generation base station in the sixth generation (6th generation, 6G) mobile communication system, the base station in the future mobile communication system or the access node in the WiFi system, etc., the evolved node B (eNB) in the long term evolution (LTE) system, the radio network controller (RNC), the node B (NB), the base station controller (BSC), the home base station (for example, home evolved NodeB, or homeNode B, HNB), the base band unit (BBU), the transmission reception point (TRP), the transmitting point (TP), the base transceiver station (BTS), etc. In a network structure, the access network device may include a centralized unit (CU) node, or a distributed unit (DU) node, or a RAN device including a CU node and a DU node, or a control plane CU node and a user plane CU node, and a RAN device of a DU node. The wireless access network device may be a macro base station, a micro base station, a relay node or a donor node, a device that provides wireless communication services for terminal devices in a V2X communication system, a wireless controller in a cloud radio access network (CRAN) scenario, a relay station, a vehicle-mounted device, a wearable device, and a network device in a future evolution network. The access network device in this embodiment may also be an open radio access network (O-RAN) device, and the O-RAN device may include an open distributed unit (O-DU) and an open centralized unit (O-CU).In the embodiments of the present application, the functions of the base station can be performed by a module (such as a chip) in the base station, or by a control subsystem including the base station functions. The control subsystem including the base station functions here can be a control center in the above-mentioned application scenarios such as smart grid, industrial control, smart transportation, and smart city. The embodiments of the present application do not limit the specific technology and specific device form adopted by the wireless access network device. For the convenience of description, the following description takes the base station as an example of the wireless access network device.

[0087] It should be noted that the above network device 140 may include multiple network devices, for example, the mobile phone 110 may send the perception result 1 to the network device 1 serving the mobile phone 110, the printer 120 may send the perception result 2 to the network device 2 serving the printer 120, and the car 130 may send the perception result 3 to the network device 3 serving the car 130. Afterwards, the network device 1 may send the perception result 1 to the network device 140, the network device 2 may send the perception result 2 to the network device 140, and the network device 3 may send the perception result 3 to the network device 140, and the data fusion is performed through the network device 140.

[0088] The purpose of environmental reconstruction is to obtain a reconstructed map. The reconstructed map is essentially a digital virtual three-dimensional space. Through this virtual three-dimensional space, objects existing in the real space can be digitally restored and reproduced. In this application, this virtual three-dimensional space is uniformly described as a reconstructed space. The objects restored in the reconstructed space are equivalent to the projections of the corresponding objects in the real space. The projections involved below all follow this meaning. In a real environment, objects such as buildings and vegetation that do not change position over time are usually called background objects. Correspondingly, objects such as vehicles and pedestrians that change position over time are called foreground objects.

[0089] Obviously, compared with background objects, foreground objects can better reflect changes in the environment. Therefore, in the process of environmental reconstruction, each UE device in multiple UE devices periodically collects perception data based on its own perspective. The perception data is usually point cloud perception data. Relying on artificial intelligence (AI) and other technologies, the perception data corresponding to the foreground object can be extracted. The perception data corresponding to the foreground object can also be called target data. The target data can be used to clarify the position of the corresponding foreground object in the environment.

[0090] It is understandable that the base station needs to maintain the reconstructed map in real time. Real-time maintenance here means that the base station instructs the corresponding UE device to compress and upload the latest extracted target data according to the update cycle of the reconstructed map when interacting with the UE device. The base station restores the projection of the foreground object corresponding to the target data in the reconstructed space based on the target data, thereby realizing environmental reconstruction.

[0091] However, each time the base station updates the reconstructed map, it only uses the target data received from the UE to restore the corresponding foreground object. This means that in order to ensure the accuracy of the reconstructed map, the UE needs to compress all the collected target data and upload it to the base station each time the map is updated. The amount of data that needs to be exchanged each time the map is updated is huge, resulting in low communication efficiency and high bandwidth load during the environment reconstruction process.

[0092] In order to solve the above technical problems, the present application provides a data processing method and related devices, aiming to improve the communication efficiency during the environment reconstruction process and reduce the bandwidth load.

[0093] The technical concept of the present application is: dividing the perception data acquired by the UE into first target data and second target data, wherein the object corresponding to the first target data has a corresponding projection in the reconstructed space, and the object corresponding to the second target data does not have a corresponding projection in the reconstructed space, and using different compression methods to compress the first target data and the second target data and upload them to the base station, wherein the compression degree corresponding to the first target data is higher than the compression degree corresponding to the second target data, thereby reducing the amount of data interacting with the base station, improving the communication efficiency during the environment reconstruction process, and reducing the bandwidth load.

[0094] Figure 2 The following is a flow chart of a data processing method provided by an embodiment of the present application. Figure 2 As shown, the UE in this embodiment is a UE that performs communication interaction when the base station updates and reconstructs the map. The data processing method in this embodiment includes the following steps:

[0095] S201, the terminal device obtains target perception data.

[0096] It is understandable that the spatial range that the sensor on the UE device can scan and perceive is limited. In this application, this limited space is referred to as the first space. A three-dimensional Cartesian coordinate system is established with the UE location as the origin. The farthest distance that the UE can perceive on each coordinate axis can form a rectangular space, which is the first space. Alternatively, with the UE location as the origin, a spherical space can be formed according to the perception radius of the sensor thereon, which is equivalent to the first space.

[0097] In this step, the target perception data is the perception data in the first space. When the sensor scans and perceives objects in the first space, for the sensor, each object is equivalent to the data aggregation of multiple scanning points. Therefore, through extraction technologies such as AI, data corresponding to foreground objects and background objects in the first space can be extracted from the target perception data.

[0098] The data corresponding to each object contains multiple data points, and each data point actually indicates the position distance of the scanning point on the surface of the object relative to the sensor. Through the target extraction network, some of the data points can constitute the bounding box data points indicating the object. Usually, these bounding boxes appear as rectangles. Therefore, the position of the object in the first space can be determined based on the bounding box information of the object. It should be noted that when the UE obtains target perception data, it usually establishes a coordinate system with the UE as the origin. The position indicated by the bounding box information of the object is the position of the object relative to the UE, and the coordinate system established by the base station in the reconstructed map is most likely different.

[0099] Therefore, before reconstructing the environment, the base station needs to determine an absolute coordinate system as the global coordinate system. The global coordinate system is the coordinate system corresponding to the reconstructed map. Usually, the global geographic coordinate system indicating longitude, latitude and altitude can be used as the global coordinate system. In order to accurately restore the projection of objects in the first space in the reconstructed map, before this step S201, the UE also needs to report the information of the first space to the base station. The information of the first space not only includes the coordinate system information corresponding to the first space, but also includes the position of the sensor carried by the UE in the first space in the first space and the perception coordinate system corresponding to the sensor.

[0100] For example: UE is a vehicle, and the sensor is a laser radar mounted on the vehicle. The laser radar is usually arranged at different positions of the vehicle and is responsible for scanning and sensing information in different directions. Therefore, the information in the first space not only includes the coordinate system information corresponding to the first space, but also needs to include the positions of multiple laser radars in the first space and their corresponding coordinate system information.

[0101] According to the rotation matrix and translation vector between different coordinate systems, or the corresponding registration algorithm, the data corresponding to the object in the first space can be converted to the global coordinate system to perform subsequent operations.

[0102] It should be noted that the UE only needs to upload the information of the first space when it interacts with the base station for the first time. The base station can use the information of the first space uploaded for the first time when it updates the reconstructed map through the UE. If the information of the first space corresponding to the UE changes, for example, the coverage range of the first space changes beyond the allowable error due to the movement of the UE and / or the change of the perception radius of the sensor carried by the UE, the UE needs to upload the changed information of the first space to the base station again.

[0103] S202: The terminal device compresses the first target data in the target perception data using a first compression method to obtain first compressed data.

[0104] S203: The terminal device compresses the second target data in the target perception data using a second compression method to obtain second compressed data.

[0105] The goal of environmental reconstruction is to restore the projection of objects in the first space in the reconstructed map. Since the compressed data received by the base station each time the reconstructed map is the data corresponding to the target object in the first space, the base station actually updates part of the reconstructed map, which is the reconstructed space corresponding to the first space in the reconstructed map.

[0106] It is understandable that the projection of some objects in the first space already exists in the reconstructed space corresponding to the first space, so this application refers to this part of the object as the first target object, and the data corresponding to the first target object is the first target data. Accordingly, the projection of the first target object in the reconstructed space corresponding to the first space is the first reconstructed object. Similarly, the remaining objects in the first space except the first target object do not yet have projections in the reconstructed space corresponding to the first space, so this part of the remaining objects is called the second target object, and the data corresponding to the second target object is the second target data. Accordingly, in this reconstructed map update, the base station will restore the projection in the reconstructed space corresponding to the first space according to the second target data, and the projection is equivalent to the second reconstructed object. It is understandable that the first target object and the second target object can be foreground objects in the first space.

[0107] There is no strict time sequence between the above steps S202 and S203. Since the update cycle of the reconstructed map is very short, the position change of the first reconstructed object relative to the first target object in the reconstructed map is usually small. The base station can consider the correlation between the data corresponding to the first reconstructed object and the first target data, thereby reducing the data volume requirement for the first target data. Therefore, the present application uses the first compression method to compress the first target data to obtain the first compressed data, and uses the second compression method to compress the second target data to obtain the second compressed data, wherein the compression ratio of the first compression method is higher than the compression ratio of the second compression method.

[0108] It should be noted that "compression" in the traditional sense refers to a data processing method that uses an algorithm to process files losslessly or losslessly in order to retain the most file information while reducing the file size. During the environmental reconstruction process, the base station needs to reconstruct the first reconstructed object corresponding to the first target object in the reconstruction space corresponding to the first space through the first target data. In other words, it is only necessary to ensure that the first compressed data obtained by compressing the first target data can be used to accurately reconstruct the first reconstructed object under the premise of improving the communication efficiency during the environmental reconstruction process. The first compression method in this application is not limited to the traditional compression processing method.

[0109] As an example, the first compression method includes: determining the posture data contained in the first target data as the first compressed data, the posture data including position data and / or posture data.

[0110] The reconstructed objects in the reconstructed map need to accurately restore the positions of the objects in the real space. It is understandable that the position of a reconstructed object such as a vehicle in the reconstructed map is not a simple point, but an area that can indicate its direction. Therefore, the first compressed data can indicate the position data and / or posture data of the first target object in the first space. Since the reconstructed map of the base station records the posture data of the first reconstructed object in the reconstructed space corresponding to the first space, the base station can update the position data and / or posture data corresponding to the first reconstructed object according to the position data and / or posture data of the first target object, so that the posture corresponding to the updated first reconstructed object is closer to the posture of the first target object in the first space.

[0111] In some implementations, the first compression method may also be: determining the difference between the pose data corresponding to the first target data and the first pose data as the first compressed data, the pose data including position data and / or posture data, and the first pose data being the pose data of the first reconstructed object in the reconstructed space. In this implementation, the base station may update the position data and / or posture data corresponding to the first reconstructed object according to the difference between the position data contained in the first target data and the first pose data, so that the updated pose corresponding to the first reconstructed object is closer to the pose of the first target object in the first space.

[0112] According to step S201, the first target data is the perception data of the first target object. The position information of the first target object can be obtained by calculating the first target data. In some implementations, the position data corresponding to the first target data can be the geometric center point data and / or geometric vertex data of the first target object. For example, after AI extraction, the frame is usually presented as a rectangle, the geometric center point data of the first target object can be the centroid coordinates of the rectangle corresponding to the first target object, and the geometric vertex data of the first target object can be the coordinates of multiple vertices of the rectangle corresponding to the first target object. The posture data can be the yaw angle data of the first target object, where the yaw angle data is the angle between the moving direction of the first target object and the horizontal axis or vertical axis in the global coordinate system.

[0113] It should be noted that when the position data corresponding to the first target data is the geometric center point data of the first target object, only the position of the first reconstructed object in the reconstructed space can be determined based on the geometric center point data of the first target object, but its orientation cannot be determined. Therefore, the first compressed data is the geometric center point data and yaw angle data corresponding to the first target data.

[0114] Since the second reconstructed object does not exist in the reconstructed space corresponding to the first space, the base station cannot restore the second reconstructed object using the same method corresponding to the first compression method above. Therefore, the second compression method adopts a conventional compression method in the prior art, such as the "Draco" compression algorithm.

[0115] S204, the terminal device sends the first compressed data, the second compressed data and the first index information to the network device.

[0116] The first compressed data includes a plurality of compressed data, each compressed data corresponds one-to-one to the first target object in the first space, and accordingly, each compressed data corresponds one-to-one to the first reconstructed object. The first index information is used to indicate that each compressed data in the first compressed data corresponds one-to-one to the first reconstructed object, and the base station can determine the first reconstructed object and its corresponding perception data and calculated data in the reconstructed space corresponding to the first space according to the first index information.

[0117] In some implementations, in addition to sending the first compressed data and the second compressed data to the network device, the terminal device also needs to send third indication information to the network device, the third indication information is used to indicate that the first target data is compressed using the first compression method, and the second target data is compressed using the second compression method, and the third indication information is also used to indicate compression parameters corresponding to the first compression method and compression parameters corresponding to the second compression method, such as quantization step size and boundary parameters. According to the third indication information, the network device uses the first compressed data and the second compressed data to update the reconstructed map.

[0118] In some implementations, the terminal device and the network device may preset a unified compression scheme. For example, when the received compressed data is only geometric center point data and yaw angle data, it may be determined that the compressed data is compressed using a first compression method, and the remaining compressed data is compressed using a "Draco" algorithm, and the corresponding compression parameters are also preset parameters. In this case, there is no need for indication information to indicate the compression method and compression parameters corresponding to each compressed data.

[0119] S205: The network device updates the reconstruction space according to the first compressed data and the second compressed data.

[0120] In this step, the second compressed data is data compressed according to a traditional compression method. Therefore, the second compressed data is decompressed to obtain complete second target data. According to the second target data, a second reconstructed object can be restored in the reconstructed space corresponding to the first space. The second reconstructed object is the projection of the second target object in the reconstructed space.

[0121] According to the difference between the pose data corresponding to the first target data and the first pose data, the position data of each point on the first reconstructed object can be updated, so that the pose corresponding to the updated first reconstructed object is closer to the pose of the first target object in the first space.

[0122] For example: the base station knows from the first compressed data that the geometric center point coordinates of the first target object corresponding to the first target data are s1, the yaw angle of the first target object is a1, and the geometric center point coordinates of the first reconstructed object are s0, and the yaw angle of the first reconstructed object is a0. Figure 3 A schematic diagram of rotating a data point provided by an embodiment of the present application is shown in FIG. Figure 3 As shown, the base station can rotate each data point on the first reconstructed object by an angle of a1-a0, and the plane coordinates of a data point p0 on the first reconstructed object are (p x0 ,p y0 ), rotate the data point by an angle of a1-a0 to obtain a new plane coordinate p1 (p x1 ,p y1 ), where p x1 =r*cos(a1),p y1 = r*sin(a1), where r is the distance from the data point to the geometric center of the first reconstructed object, The coordinates obtained by the rotation are then translated by a distance of s1-s0 to obtain the position corresponding to the data point. The above operation is performed for each data point on the first reconstructed object to update the position data of each point on the first reconstructed object.

[0123] According to the above operations, the first reconstructed object and the second reconstructed object are restored to update the reconstructed space.

[0124] In this embodiment, different compression methods are used to compress the first target data and the second target data and upload them to the base station, so as to minimize the amount of data required to update the first reconstructed object, thereby reducing the amount of data interacting with the base station, improving the communication efficiency in the process of environmental reconstruction, and reducing the bandwidth load. At the same time, since the base station uses the correlation between the first target data and the data corresponding to the first reconstructed object when updating the reconstructed map, the objects in the UE's perception blind area can be retained in the reconstructed map, thereby improving the accuracy of the reconstructed map.

[0125] Figure 2 In the illustrated embodiment, the UE needs to use different compression processing methods for the first target data and the second target data. Therefore, the UE first needs to distinguish the first target data and the second target data in the target perception data. The following introduces a method for the UE to distinguish the first target data and the second target data. Figure 4A flowchart of a data processing method provided by an embodiment of the present application, in a possible implementation manner, as follows Figure 4 As shown, before step S202, the data processing method provided in this embodiment further includes steps S202-0 and S202-1:

[0126] S202-0, the terminal device receives first indication information from the network device, the first indication information includes at least one target data, the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstructed space, each target data in the at least one target data includes posture data of the corresponding reconstructed object, and the posture data includes position data and / or posture data.

[0127] In this step, the base station sends the first indication information to the UE, and the first indication information includes the pose data of the reconstructed object in the reconstructed space corresponding to the first space, and the pose data includes position data and / or attitude data. It should be noted that, since there is a blind spot in the scanning perception range of the UE, the pose data of the reconstructed object in the reconstructed space indicated in the first indication information includes not only the pose data of the first reconstructed object, but also the pose data of the reconstructed object in the UE perception blind spot, and the data corresponding to the first reconstructed object is equivalent to the third target data.

[0128] according to Figure 2 It can be seen from the illustrated embodiment that each reconstructed object in the reconstructed map is actually an aggregation of multiple data points, and these multiple data points are equivalent to the complete data of the reconstructed object. The base station saves the complete data of each reconstructed object in the reconstructed map. Since the reconstructed object is an object restored by the base station based on the target perception data uploaded by the UE, when the position data corresponding to the first target data uploaded by the UE is the geometric center data and / or geometric vertex data of the first target object, the position data corresponding to the reconstructed object includes the geometric center data and / or geometric top and bottom data of the reconstructed object. Similarly, when the posture data corresponding to the first target data uploaded by the UE is the yaw angle data of the first target object, the posture data corresponding to the reconstructed object includes the yaw angle data.

[0129] Accordingly, in a possible implementation, the position data of the reconstructed object contained in the first indication information is geometric center point data and / or geometric vertex data of the reconstructed object, and the posture data of the reconstructed object contained in the first indication information is yaw angle data of the reconstructed object.

[0130] It should be noted that when the position data in the first indication information is the geometric center point data of the reconstructed object, the geometric center point data of the reconstructed object can only determine its position in the reconstructed space, but its orientation cannot be determined. Therefore, the first indication information needs to include the geometric center point data and yaw angle data of the reconstructed object.

[0131] When the position data in the first indication information is the geometric vertex data of the reconstructed object, since the schematic bounding box of the reconstructed object is a rectangle, the geometric center point data and yaw angle data of the reconstructed object can also be determined according to the shape characteristics of the rectangle. Therefore, the first indication information may only include the geometric vertex data of the reconstructed object.

[0132] In some implementations, if the downlink resources during communication interaction between the base station and the UE are sufficient, the base station may also send complete data of all reconstructed objects in the reconstructed space to the UE through the first indication information.

[0133] S202-1, the terminal device determines first target data and second target data from the target perception data according to the first indication information.

[0134] It should be noted that since the update cycle of the reconstructed map is very short, the position of the first target object in the first space and the position of the first reconstructed object in the reconstructed space corresponding to the first space are very small. Therefore, the UE first calculates the posture data corresponding to each target data in the multiple target data according to the target perception data, and compares the posture data contained in the first indication information with the nearby posture data obtained by calculation, so as to determine the first target data and the second target data in the target perception data.

[0135] As an example, the coordinates of the geometric center point of the reconstructed object 1 in the reconstructed space are s0, which is the coordinate in the global coordinate system, and the yaw angle of the reconstructed object 1 is a0. By calculating the target perception data, it can be seen that there is a foreground object 2 with a geometric center point coordinate s1 near the coordinate s0 in the first space, and the yaw angle of the foreground object 2 is a1. Comparing the yaw angle a1 of the foreground object 2 and the yaw angle a0 of the reconstructed object 1, if the value of a1-a0 is less than the yaw angle threshold Δa, it indicates that the moving direction of the foreground object 2 is consistent with the moving direction of the reconstructed object 1, where the yaw angle threshold is equivalent to the attitude difference threshold. On the basis of judging that the moving directions are consistent, the geometric center point s1 of the foreground object 2 and the geometric center point s0 of the reconstructed object 1 are further calculated. If the value of s1-s0 is less than the first distance threshold T1, it can be judged that the foreground object 2 is the first target object in the first space, and the perception data corresponding to the foreground object 2 is the first target data in the target perception data.

[0136] In some implementations, the first indication information may also indicate the coordinates of some geometric vertices and the yaw angle of the reconstructed object 1 in the reconstructed space, and the coordinates of the geometric vertices are also coordinates in the global coordinate system. There is a foreground object 2 near the corresponding geometric vertex coordinates in the first space. The yaw angle of the foreground object 2 is compared with the yaw angle of the reconstructed object 1. If the difference between the two is less than the yaw angle threshold Δa, it indicates that the moving direction of the foreground object 2 is consistent with the moving direction of the reconstructed object 1. On the basis of judging that the moving directions are consistent, the head frame and the tail frame of the object can be defined, wherein the head frame is the frame pointing to the same side of the moving direction from the geometric center point of the object, and the tail frame and the geometric center point of the object point to the opposite side of the moving direction. If the tail frame of the foreground object 2 and the head frame of the reconstructed object 1 have an intersection, it can be judged that the foreground object 2 is the first target object in the first space, and the perception data corresponding to the foreground object 2 is the first target data in the target perception data. It can be understood that judging whether the frames have an intersection is actually a deformation method for calculating and judging the difference between the geometric center points.

[0137] Obviously, in the above implementation, when the pose calculation between the foreground object and the reconstructed object does not meet the preset judgment condition, the foreground object can be judged as the second target object in the first space, and its corresponding perception data is the second target data in the target perception data.

[0138] In the above embodiments, the base station only needs to obtain the position data of the first target object through the first compressed data sent by the UE, so as to update the first reconstructed object in the reconstructed space. However, in order to meet the performance requirements of the reconstructed map or the performance requirements of specific tasks such as obstacle avoidance, it is necessary to improve the accuracy of the reconstructed map while improving the communication efficiency. The following describes how to Figure 4 The reconstruction performance is improved based on the illustrated embodiment.

[0139] Figure 5 A flowchart of a data processing method provided by an embodiment of the present application is shown in FIG. Figure 5 As shown, in step S202-0, the third target information in the first indication information sent by the base station to the UE also includes a small amount of sampling point data of the first reconstructed object. The sampling point data is equivalent to auxiliary information, which can further refine the first target data. Therefore, this embodiment also needs to include steps S202-2 and S202-3:

[0140] S202-2: The terminal device determines a first neighbor distance between the first reconstructed object and the first target object according to the sampling point data included in the third target data, where the first neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object.

[0141] According to step S202-0, the first reconstructed object is actually an aggregation of multiple data points. Usually, 2% to 5% of the data points are taken as sampling point data. According to the geometric center point data and yaw angle data corresponding to the first target data, each sampling point data is reconstructed according to Figure 3 The first target data, as the perception data of the first target object, also includes multiple data points. Each of the updated multiple sampling points can calculate the distance with each of the multiple data points in the first target data. Each updated sampling point can obtain the shortest distance with the data point in the first target data by calculation. The multiple shortest distances obtained from the updated multiple sampling points are averaged. The average is the first nearest neighbor distance between the first reconstructed object and the first target object. The first nearest neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object.

[0142] For example, the sampling point data of the first reconstructed object includes 5 sampling points, and the first target data includes 100 data points. According to the geometric center point data and the yaw angle data corresponding to the first target data, the 5 sampling points are rotated and translated to obtain 5 updated sampling points. Then, the distance between each of the 5 updated sampling points and the 100 data points is calculated respectively until the shortest distance between each sampling point and the data point in the first target data is determined. The 5 updated sampling points can obtain 5 shortest distances, and the average value of the 5 shortest distances is calculated. The average value is the first nearest neighbor distance between the first reconstructed object and the first target object in this step. The first nearest neighbor distance can be used to indicate the shortest distance between the first reconstructed object and the first target object.

[0143] S202-3, compress the fourth target data using a third compression method to obtain third compressed data.

[0144] According to the first neighbor distance obtained in step S202-2, the first target object can be further subdivided. If the first neighbor distance corresponding to the first target object 1 is not greater than the second distance threshold T2, the first target data corresponding to the first target object 1 is compressed using the first compression method to obtain first compressed data.

[0145] If the first nearest neighbor distance corresponding to the first target object 2 is greater than the distance threshold T2, then the first target object 2 is not only the first target object, but also the fourth target object in the first target object, and the first nearest neighbor distance corresponding to the fourth target object is greater than the distance threshold T2. For the first target object 2, the posture data corresponding to the first target object 2 is first determined as the first compressed data, and the fourth target data is compressed using the third compression method to obtain the third compressed data, wherein the fourth target data is the perception data corresponding to the first target object 2, that is, the first target data corresponding to the first target object 2.

[0146] It is understandable that after executing step S202-3, Figure 5 In step S204 shown, the UE also needs to send the third compressed data to the network device. To ensure communication efficiency, the compression ratio of the third compression method is higher than that of the second compression method. The first compressed data, the second compressed data, and the third compressed data can be directly sent to the base station. In some implementations, if the uplink resources when the UE and the base station communicate are limited, the UE can choose layered incremental transmission, that is, first send the first compressed data and the second compressed data to the base station, and then send the third compressed data in an incremental layer.

[0147] In addition, for the first target object 2, the base station not only receives the first compressed data corresponding to the first target object 2, but also receives the third compressed data corresponding to the first target object 2. Figure 5 In step S205 shown, for the first reconstructed object corresponding to the first target object 2, the base station needs to perform fusion update according to the corresponding first compressed data and third compressed data.

[0148] In some implementations, before step S202-0, the UE may send a first request message to the base station according to the performance requirements of the reconstructed map or the performance requirements of a specific task, and the first request message is used to request the sampling point data of all reconstructed objects contained in the reconstructed space. At the same time, the first request message may also carry compression level information, and the compression level information indicates the requirements for the degree of compression. The lower the compression level requirement, the more information needs to be retained in the compressed data, and the higher the performance requirements for the reconstructed map. The base station may determine whether to send the sampling point data of all reconstructed objects in the reconstructed space according to the compression level information carried by the first request message. It can be understood that the second distance threshold T2 can be set by the base station according to the performance requirements, or it can be set by the UE itself.

[0149] It should be noted that, for regular objects such as vehicles, except for the bottom surface close to the ground, the sensing data can actually indicate the outer surfaces of the vehicle in different directions. Therefore, in some implementations, the sampling point data of the first reconstructed object in step S202-2 may be the sampling point data indicating the first outer surface on the first reconstructed object, and the first outer surface includes at least one outer surface on the first reconstructed object, that is, the sampling point data of the first reconstructed object may indicate the sampling point data of different outer surfaces on the first reconstructed object. Accordingly, when calculating the first nearest neighbor distance between the first reconstructed object and the first target object, it is necessary to calculate the first nearest neighbor distance between the first outer surface of the first reconstructed object and the second outer surface of the first target object, wherein the second outer surface of the first target object and the first outer surface of the first reconstructed object are one-to-one corresponding outer surfaces. In this implementation, the first nearest neighbor distance can be calculated for different outer surfaces respectively, and for the first target data corresponding to each outer surface, it can be determined whether the third compression mode needs to be used respectively, and the first target object can be further subdivided in units of faces, and the compressed data can be sent with finer granularity, thereby improving the reconstruction quality.

[0150] In this application, the sampling point data of the reconstructed object sent by the base station is used as auxiliary information, and the first target data is further subdivided and compressed, so as to further improve the accuracy of the reconstructed map while ensuring communication efficiency, and meet the high reconstruction performance requirements in different scenarios.

[0151] In the above embodiment, the UE needs to determine the first target data and the second target data from the target perception data through the first indication information sent by the base station. In some implementations, the base station can determine the first target data and the second target data from the target perception data. Figure 6 The following is a flow chart of a data processing method provided by an embodiment of the present application. Figure 6 As shown, in Figure 2 On the basis of the embodiment shown, before step S202, the data processing method provided in this embodiment further includes steps S201-1, S201-2 and S201-3, which are specifically as follows:

[0152] S201-1, the terminal device sends the posture data corresponding to each target data in the target perception data to the network device, and the multiple target data correspond one-to-one to the multiple target objects in the first space.

[0153] In this step, the UE sends the posture data corresponding to each target data in the multiple target data in the target perception data to the base station, each target data is the perception data of the corresponding object in the first space, and the posture data corresponding to each target data includes position and / or posture data.

[0154] In some implementations, the position data corresponding to each target data is the geometric center point data and / or geometric vertex data of the corresponding object in the first space, and the posture data corresponding to each target data is the yaw angle data of the corresponding object in the first space.

[0155] When the position data corresponding to the target data is the geometric center point data of the corresponding object in the first space, only the position of the corresponding reconstructed object in the reconstructed space can be determined based on the geometric center point data of the object, but its orientation cannot be determined. Therefore, the posture data corresponding to each target data includes geometric center point data and yaw angle data.

[0156] When the position data corresponding to the target data is the geometric vertex data of the corresponding object in the first space, since the schematic bounding box of the object is a rectangle, the geometric center point data and yaw angle data of the object can also be determined according to the shape characteristics of the rectangle. Therefore, the position data corresponding to each target data can only include the geometric vertex data of the corresponding object.

[0157] S201 - 2 , the network device determines first target data and second target data from multiple target data.

[0158] This step is Figure 4 Step S202-1 in the illustrated embodiment is similar, the difference being that in step S202-1 the UE determines the first target data and the second target data from the target perception data, while in this step the base station determines the first target data and the second target data from the target perception data. The specific judgment method is the same as that in step S202-1 and will not be repeated here.

[0159] S201-3, sending first indication information to the terminal device, where the first indication information is used to indicate first target data and second target data among multiple target data.

[0160] In step S201-2, the base station has determined the first target data and the second target data among the multiple target data, and sends the above distinction information to the UE through the first indication information. The UE can select different compression methods to compress the first target data and the second target data.

[0161] In some implementations, the first indication information may also directly indicate that the first target data is compressed using the first compression method and the second target data is compressed using the second compression method. The UE may directly compress the first target data and the second target data according to the first indication information.

[0162] It should be noted that the base station can determine the first target data and the second target data from multiple target data, which means that the base station can determine the first reconstructed object from all reconstructed objects in the first space. Therefore, the UE can send a second request information to the base station according to the performance requirements of the reconstructed map or the performance requirements of a specific task. The second request information is used to request the sampling point data of the first reconstructed object in the reconstructed space. Figure 6 In the embodiment shown, after the base station sends the sampling point data of the first reconstructed object, the UE can Figure 5 In the steps of the illustrated embodiment, the first target data is further subdivided using the sampling point data.

[0163] In the above embodiments, there are multiple UEs in the environment reconstruction process, and the base station updates the reconstructed map by fusing data from multiple UEs. The data processing method proposed in this application is also applicable to single UE timing scenarios.

[0164] Figure 2 In step S201 of the illustrated embodiment, the UE obtains target perception data. Since the UE periodically collects perception data, the target perception data is the perception data collected by the UE most recently. In the above embodiments, the data corresponding to the reconstructed object in the reconstructed space are required to determine the first target data and the second target data in the target perception data. It can be understood that in a single UE scenario, before the base station updates the reconstructed map, the data corresponding to the reconstructed object in the reconstructed space is essentially the data collected and uploaded by the UE during the last collection cycle.

[0165] Therefore, for a single UE, the UE can obtain the target perception data collected in the previous collection cycle and stored locally. According to the target perception data of the previous collection cycle, the UE can determine the first target data and the second target data from the target perception data collected in the current collection cycle. It should be noted that since the target perception data collected in the previous collection cycle is complete perception data indicating the first target object and the second target object in the first space, the UE can also design residual coding for the target perception data collected in the current collection cycle. The residual coding here refers to: for each data point in the first target data collected in the previous collection cycle, find a neighboring point with the shortest distance in the first target data collected in the current collection cycle, calculate the residual between each data point in the first target data in the previous collection cycle and its corresponding neighboring point, and quantize and encode the residual value. Since the residual value is smaller than the range indicated by the complete perception value, the quantization parameter used is also smaller, and the data capacity of the obtained residual coding is also smaller. Therefore, the residual coding data of the first target data collected in the previous collection cycle and the posture data corresponding to the first target data can be determined as the first compressed data.

[0166] It can be understood that in step S205, since the data corresponding to the reconstructed object in the reconstructed space is the data collected and uploaded by the UE in the last collection cycle, the first reconstructed object corresponding to the first target data can be updated according to the residual coding data in the first compressed data, and the updating method of the second reconstructed object is consistent with the aforementioned embodiment.

[0167] In this embodiment, in a single UE timing scenario, the first target data and the second target data in the target perception data can be determined through the local historical data saved by the UE. The data processing method proposed in this application can also improve the communication efficiency between the UE and the base station, and expand the scenarios in which environmental reconstruction can be applied.

[0168] Figure 7 The following is a simulation diagram of a data processing method provided by an embodiment of the present application. Figure 7 As shown, there are 14 target objects in the environment, of which 3 are mobile UEs. When the base station updates the reconstructed map corresponding to the environment, the base station interacts with the 3 mobile UEs in an interlaced manner. This update undergoes 24 update moments. The following compares the difference in communication data volume between the data processing method proposed in this application and the existing data processing method.

[0169] Figure 8 A schematic diagram of a simulation comparison between a data processing method provided in an embodiment of the present application and an existing data processing method. In this environment, the moving speed of UE 1 is 5 m / s (meters per second), the moving speeds of UE 2 and UE 3 are 7 m / s, and different UEs are in opposite or perpendicular positions. The UE scanning perception period in this simulation is 0.3 s.

[0170] In the existing data processing method, the UE directly performs "Draco" compression on the perception data corresponding to the target object sensed by the scan, and the corresponding compression parameter "qp" is 3 to 5. The larger the "qp", the smaller the degree of compression of the perception data, and accordingly, the better the reconstruction performance in the process of environmental reconstruction. Similarly, the smaller the "qp", the greater the degree of compression of the perception data, and accordingly, the worse the reconstruction performance in the process of environmental reconstruction. According to the data processing method proposed in the present application, the geometric center point and yaw angle data in the first target data are determined as the first compressed data, and the second target data is also compressed by "Draco" compression, and the corresponding compression parameter "qp" is 3.

[0171] like Figure 8As shown in Figure (A), the horizontal axis represents the update time, and the vertical axis represents the number of target objects. The 0th moment is equivalent to the initial moment. At this time, all the target objects in the first space are second target objects. It can be understood that the UE excludes itself when acquiring the target perception data. Therefore, at the initial moment, there are 13 second target objects in the first space. The target perception data acquired by the UE are all second target data. The perception data corresponding to the 13 target objects need to be compressed using the second compression method. As time goes by, the base station updates the reconstructed map, and the second target object is projected in the reconstructed space to obtain the second reconstructed object. At the next update moment, some target objects in the first space are transformed from second target objects to first target objects. Accordingly, the target data in the target perception data acquired by the UE is transformed from second target data to first target data. According to Figure 8 As shown in Figure (A), at the third moment, all target objects in the environment have been reconstructed in the reconstructed space. Therefore, in the subsequent moments, the UE compresses all target data except its own using the first compression method. Considering that there are blind spots in the scanning perception range of the UE, the number of target objects scanned and perceived in the figure will change over time.

[0172] like Figure 8 As shown in (B) in FIG. 1 , the horizontal axis represents the update time, and the vertical axis represents the data transmission amount of each update, and its unit is kilobyte (KB). Since the UE uses the first compression method to compress all target data except itself after the third moment, according to Figure 8 As can be seen from Figure (B), after the third moment, the UE only needs to transmit a very small amount of data. However, for the existing data processing method, since the data corresponding to each target object needs to be compressed and uploaded, the amount of data that needs to be transmitted for each update is affected by the number of target objects sensed by the UE scan.

[0173] like Figure 8 As shown in Figure (C), the horizontal axis represents the update time, and the vertical axis represents the cumulative data transmission amount, and its unit is KB. Since the UE uses the first compression method to compress all target data except itself after the third moment, according to Figure 8 As can be seen from Figure (C), the slope of the line after the third moment is much smaller than that of the first three moments. For the existing data processing method, the amount of data that needs to be transmitted for each update does not change much, so the cumulative data transmission volume increases steadily, and the corresponding line slope changes very little. As of the last update moment, the data processing method proposed in this application can reduce the cumulative data volume by about 85% compared with the existing data processing method.

[0174] like Figure 8As shown in Figure (D), the horizontal axis represents the amount of data sent, and the vertical axis represents the normalized mean square error (NMSE). The NMSE can indicate the reconstruction performance. It can be seen from the figure that when the NMSE is 10 -5 Under the reconstruction performance of the order of magnitude, the data processing method proposed in this application can reduce the data volume by 80% to 86% compared with the existing data processing method. Since the base station also needs to send the first indication information to the UE, the average downlink overhead required for the first indication information is 0.086KB, which accounts for about 20% of the uplink compressed data, while compared with the existing data processing method, it accounts for about 3.6% of its uplink compressed data.

[0175] It should be noted that the reconstruction performance in the environment reconstruction process is related to the target distance perceived by the UE scanning. In this simulation, the target distance is far and the collection points are sparse, which has a certain impact on the reconstruction performance.

[0176] Figure 8 In the illustrated embodiment, the base station does not send down the sampling point data of the reconstructed object. The following describes a simulation comparison for implementing further refinement processing based on the sampling point data.

[0177] Fig. 9 A simulation comparison diagram between a data processing method provided by an embodiment of the present application and an existing data processing method. In this environment, the moving speed and scanning perception cycle of the three mobile UEs remain unchanged. In the existing data processing method, the UE directly performs "Draco" compression on the perception data corresponding to the target object sensed by the scan, and the corresponding compression parameter "qp" is 4 to 8.

[0178] In this simulation, the second target data is also compressed using "Draco", and the corresponding compression parameter "qp" is 4 to 8. The base station provides 2% to 5% of the sampling point data of the reconstructed object. The sampling point data of the reconstructed object is used to further refine the first target data, and the geometric center point and yaw angle data in the first target data are determined as the first compressed data. The fourth target data is compressed using "Draco", and its corresponding compression parameter "qp" is dynamically selected between 3 and 7 according to the calculation results of the sampling point data.

[0179] like Fig. 9 As shown in Figure (A), the horizontal axis represents the update time and the vertical axis represents the number of target objects. Figure 8 Similar to Figure (A) in FIG. 1 , in this embodiment, the sampling point data is used as auxiliary information, and the fourth target data needs to be compressed using the third compression method. It should be noted that the target object corresponding to the fourth target data is the fourth target object. Fig. 9Figure (A) in the figure distinguishes the fourth target object from other first target objects. The fourth target object belongs to the third compression method in the figure, and the other objects in the first target objects belong to the first compression method.

[0180] like Fig. 9 As shown in Figure (B), the horizontal axis represents the update time, and the vertical axis represents the amount of data sent for each update, and its unit is KB. Since the fourth target data is also compressed using "Draco", but its corresponding compression parameter "qp" is 3 to 7, compared with the compression parameter "qp" of 4 to 8 in the existing data processing method, the compression degree corresponding to the fourth target data is higher, so the amount of data sent for each update is lower.

[0181] like Fig. 9 As shown in Figure (C), the horizontal axis represents the update time, and the vertical axis represents the cumulative data transmission amount, and its unit is KB. Since the first target data is refined by relying on the sampling point data in this embodiment, compared with Figure 8 In the embodiment shown, the amount of data that needs to be uploaded increases, so the slope of the cumulative data transmission volume does not change significantly. As of the last update, the data processing method proposed in this application can reduce the cumulative data volume by about 17% compared with the existing data processing method.

[0182] like Fig. 9 As shown in Figure (D), the horizontal axis represents the amount of data sent, and the vertical axis represents NMSE. It can be seen from the figure that when NMSE is 10 -7 With the reconstruction performance of the same order of magnitude, the data processing method proposed in the present application can reduce the data volume by 12% to 32% compared with the existing data processing method. Since the first indication information sent by the base station also includes sampling point data, the average downlink overhead required for the first indication information is 0.1224KB, which accounts for about 3.5% of the uplink compressed data, while compared with the existing data processing method, it accounts for about 3.2% of its uplink compressed data.

[0183] It should be noted that, after confirming that the object in the first space is the first target object, the base station may no longer send the sampling point data of the first reconstructed object at the subsequent update time. For the first target data, the UE uses the sampling point data of the first reconstructed object sent previously, thereby determining the fourth target data in the first target data, which can reduce the downlink overhead required to send the first indication information. When the UE needs to send the third compressed data, the UE can merge the third target data sent by the base station with the first target data at the current update time to obtain the merged first target data, and determine the fourth target data based on the merged first target data.

[0184] It can be seen from the simulation in the above embodiments that the data processing method proposed in this application can reduce the amount of communication data between the UE and the base station while ensuring reconstruction performance, thereby improving communication efficiency and reducing bandwidth load.

[0185] Fig.10 This is a schematic diagram of the structure of a data processing device provided by an embodiment of the present application. Fig.10 As shown, the apparatus 1000 of this embodiment may include: a sensing module 1001, a receiving module 1002, a processing module 1003 and a sending module 1004. The apparatus 1000 may be used to implement Figure 2 or Figures 4 to 6 The operations implemented by the terminal device in the method.

[0186] For example, the perception module 1001 can be used to obtain target perception data.

[0187] The receiving module 1002 can be used to receive first indication information from a network device, the first indication information includes at least one target data, the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstructed space, each target data in the at least one target data corresponds to the posture data of the reconstructed object, and the posture data includes position data and / or posture data.

[0188] The processing module 1003 can be used to compress the first target data in the target perception data using a first compression method to obtain first compressed data. The processing module 1003 can also be used to compress the second target data in the target perception data using a second compression method to obtain second compressed data.

[0189] The sending module 1004 may be configured to send the first compressed data, the second compressed data, and the first index information to the network device, where the first index information is used to indicate that the first compressed data corresponds one-to-one to the first reconstructed object.

[0190] Fig.11 This is a schematic diagram of the structure of a data processing device provided by another embodiment of the present application. Fig.11 As shown, the apparatus 1100 of this embodiment may include: a sending module 1101, a receiving module 1102, a processing module 1103 and a reconstruction module 1104. The apparatus 1100 may be used to implement Figure 2 or Figures 4 to 6 The operations implemented by the network device in the method.

[0191] For example, the sending module 1001 can send a first indication message to the terminal device, the first indication message includes at least one target data, the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstruction space, each target data in the at least one target data corresponds to the posture data of the reconstructed object, and the posture data includes position data and / or posture data.

[0192] The receiving module 1002 may be configured to receive first compressed data, second compressed data, and first index information from a terminal device, wherein the first index information is used to indicate that the first compressed data corresponds one-to-one to the first reconstructed object.

[0193] The processing module 1103 may be configured to determine first target data and second target data from a plurality of target data in the target perception data.

[0194] The reconstruction module 1104 may be configured to update the reconstruction space according to the first compressed data and the second compressed data.

[0195] It should be understood that the apparatus 1000 and the apparatus 1100 are embodied in the form of functional modules. The term "module" may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (e.g., a shared processor, a dedicated processor, or a group processor, etc.) and a memory for executing one or more software or firmware programs, a combined logic circuit, and / or other suitable components that support the described functions.

[0196] The above-mentioned apparatus 1000 and apparatus 1100 have the function of implementing the corresponding processes and / or steps in the above-mentioned method embodiments; the above-mentioned functions can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-mentioned functions.

[0197] Fig.12 A schematic diagram of the structure of a data processing device provided in yet another embodiment of the present application. Fig.12 The device 1200 shown can be used to execute any of the aforementioned methods performed by a terminal device or a network device.

[0198] like Fig.12 As shown, the device 1200 of this embodiment includes: a memory 1201, a processor 1202, a communication interface 1203 and a bus 1204. The memory 1201, the processor 1202 and the communication interface 1203 are connected to each other through the bus 1204.

[0199] The memory 1201 may be a read only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM). The memory 1201 may store a program, and when the program stored in the memory 1201 is executed by the processor 1202, the processor 1202 is used to execute any of the aforementioned methods.

[0200] The processor 1202 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit, or one or more integrated circuits to execute related programs.

[0201] The processor 1202 may also be an integrated circuit chip with signal processing capability. In the implementation process, each relevant step in the embodiment of the present application may be completed by an integrated logic circuit of hardware in the processor 1202 or by instructions in the form of software.

[0202] The processor 1202 may also be a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0203] The steps of the method disclosed in the embodiment of the present application can be directly embodied as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 1201, and the processor 1202 reads the information in the memory 1201, and completes the functions required to be performed by the units included in the device of the present application in combination with its hardware.

[0204] The communication interface 1203 may use, but is not limited to, a transceiver or other transceiver device to implement communication between the apparatus 1200 and other devices or apparatuses.

[0205] The bus 1204 may include a path for transmitting information between various components of the device 1200 (eg, the memory 1201 , the processor 1202 , and the communication interface 1203 ).

[0206] The embodiment of the present application also provides a computer-readable storage medium, in which computer instructions are stored. When a processor executes the computer instructions, each step of the method in the above embodiment is implemented.

[0207] The embodiment of the present application also provides a computer program product, including computer instructions, which implement the various steps of the method in the above embodiment when executed by a processor.

[0208] It should be noted that the modules or components shown in the above embodiments may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits, or one or more microprocessors, or one or more field programmable gate arrays, etc. For another example, when a certain module above is implemented in the form of a processing element calling a program code, the processing element may be a general-purpose processor, such as a central processing unit or other processor that can call a program code, such as a controller. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0209] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, software module or any combination thereof. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrated. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk (SSD)), etc.

[0210] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0211] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A data processing method, applied to a terminal device, characterized in that: The method comprises: Acquire target perception data, where the target perception data is perception data of a target object in the first space where the terminal device is located; Using a first compression method to compress first target data in the target perception data to obtain first compressed data, wherein the first target data is perception data of a first target object in the first space, and a reconstruction space corresponding to the first space includes a first reconstructed object corresponding to the first target object; The first compressed data and first index information are sent to a network device, where the first index information is used to indicate that the first compressed data corresponds to the first reconstructed object.

2. The method according to claim 1, characterized in that Before compressing the first target data in the target perception data using the first compression method to obtain the first compressed data, the method further includes: receiving first indication information from the network device, where the first indication information is used to determine the first target data; The first target data is determined from the target perception data according to the first indication information, and the first index information is acquired according to the first indication information.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: Using a second compression method to compress second target data in the target perception data to obtain second compressed data, wherein the second target data is perception data of a second target object in the first space, and the reconstructed space does not include a second reconstructed object corresponding to the second target object; The second compressed data is sent to the network device.

4. The method according to any one of claims 1 to 3, characterized in that The first compression method includes: determining the posture data corresponding to the first target data as the first compressed data, and the posture data includes position data and / or posture data.

5. The method according to any one of claims 1 to 3, characterized in that The first compression method includes: determining the difference between the posture data corresponding to the first target data and the first posture data as the first compressed data, the posture data includes position data and / or posture data, and the first posture data is the posture data of the first reconstructed object in the reconstruction space.

6. The method according to claim 4 or 5, characterized in that: The position data includes geometric center point data and / or geometric vertex data, and the posture data includes yaw angle data.

7. The method according to claim 2, characterized in that: The first indication information includes at least one target data, the at least one target data corresponds one-to-one to at least one reconstructed object included in the reconstructed space, each target data in the at least one target data includes position data of the corresponding reconstructed object, and the position data includes position data and / or posture data; The determining the first target data from the target perception data according to the first indication information includes: Acquire posture data corresponding to each target data in the target perception data, wherein a difference between a posture indicated by the posture data corresponding to the first target data and a posture indicated by the posture data in the third target data in the at least one target data is less than a posture difference threshold, and / or a distance between the position data corresponding to the first target data and the position data in the third target data is less than a first distance threshold, and the third target data corresponds to the first reconstructed object.

8. The method according to claim 7, characterized in that The third target data further includes sampling point data of the first reconstructed object, where the sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on the first reconstructed object; Wherein, the method further comprises: determining a first neighbor distance between the first reconstructed object and the first target object according to the sampling point data included in the third target data, wherein the first neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object; Using a third compression method to compress fourth target data to obtain third compressed data, the fourth target data is perception data of a fourth target object among the first target objects, the first nearest neighbor distance corresponding to the fourth target object is greater than or equal to a second threshold, and the compression ratio of the third compression method is higher than that of the second compression method; The third compressed data is sent to the network device.

9. The method according to claim 8, characterized in that The sampling point data of the first reconstructed object is used to indicate the position data of each point of at least one point on the first reconstructed object, including: The sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on a first outer surface of the first reconstructed object, wherein the first outer surface includes at least one outer surface on the first reconstructed object; The first neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object, including: The first neighbor distance is used to indicate the shortest distance between a first outer surface on the first reconstructed object and a second outer surface on the first target object, where the second outer surface is an outer surface on the first target object corresponding to the first outer surface on the first reconstructed object.

10. The method according to claim 8 or 9, characterized in that: Before receiving the first indication information from the network device, the method further includes: Sending first request information to the network device, where the first request information is used to request sampling point data of the reconstructed object contained in the reconstructed space; Wherein, each target data includes sampling point data of the corresponding reconstructed object.

11. The method according to any one of claims 8 to 10, characterized in that The first indication information is also used to indicate the second distance threshold.

12. The method according to claim 3, characterized in that The receiving first indication information from the network device includes: Sending to the network device the posture data corresponding to each target data in the target perception data, wherein the multiple target data correspond one-to-one to the multiple target objects in the first space; First indication information is received from the network device, where the first indication information is used to indicate the first target data and the second target data among the multiple target data.

13. The method according to claim 12, characterized in that The first indication information is further used to instruct that the first target data be compressed using the first compression method, and the first indication information is further used to instruct that the second target data be compressed using the second compression method.

14. The method according to claim 12 or 13, characterized in that Before receiving the first indication information from the network device, the method further includes: Sending second request information to the network device, where the second request information is used to request the sampling point data of the first reconstructed object.

15. The method according to claim 1, characterized in that The first compression method includes: determining the residual coding data of the first target data and the posture data corresponding to the first target data as the first compressed data, and the posture data includes position data and / or posture data.

16. The method according to any one of claims 1 to 15, characterized in that The method further comprises: Send third indication information to the network device, wherein the third indication information is used to indicate that the first target data is compressed using the first compression method and that the second target data is compressed using the second compression method, and the third indication information is also used to indicate compression parameters of the first compression method and compression parameters of the second compression method.

17. A data processing method, applied to a network device, characterized in that: The method comprises: receiving first compressed data from a terminal device, where the first compressed data is data obtained by first target data being processed in a first compression manner, the first target data is perception data of a first target object in a first space, and a reconstruction space corresponding to the first space includes a first reconstructed object corresponding to the first target object; The reconstruction space is updated according to the first compressed data.

18. The method according to claim 17, characterized in that The method further comprises: receiving second compressed data from a terminal device, where the second compressed data is data obtained by second compression processing of second target data, the second target data is perception data of a second target object in the first space, and the reconstructed space does not include a second reconstructed object corresponding to the second target object; The reconstruction space is updated according to the second compressed data.

19. The method according to claim 17 or 18, characterized in that The first compression method includes: determining the posture data corresponding to the first target data as the first compressed data, and the posture data includes position data and / or posture data.

20. The method according to claim 19, characterized in that The updating of the reconstruction space according to the first compressed data comprises: According to the difference between the pose data corresponding to the first target data and the first pose data, the position data of each point on the first reconstructed object in the reconstruction space is updated, and the first pose data is the pose data of the first reconstructed object.

21. The method according to any one of claims 17 to 20, characterized in that Before receiving the first compressed data from the terminal device, the method further includes: Sending first indication information to the terminal device, where the first indication information is used to determine the first target data.

22. The method according to claim 21, characterized in that The first indication information includes at least one target data, and the at least one target data corresponds one-to-one to at least one reconstructed object contained in the reconstruction space. Each target data in the at least one target data includes posture data of the corresponding reconstructed object, and the posture data includes position data and / or posture data.

23. The method according to claim 22, characterized in that The third target data in the at least one target data further includes sampling point data of the first reconstructed object, the sampling point data of the first reconstructed object is used to indicate the position data of each point in the at least one point on the first reconstructed object, and the third target data corresponds to the first reconstructed object; The method further comprises: Receive third compressed data from the terminal device, where the third compressed data is data obtained by processing fourth target data by a third compression method, the fourth target data is perception data of a fourth target object among the first target objects, the first neighbor distance corresponding to the fourth target object is greater than or equal to a second threshold, and the compression ratio of the third compression method is higher than that of the second compression method.

24. The method according to claim 23, characterized in that The sampling point data of the first reconstructed object is used to indicate the position data of each point of at least one point on the first reconstructed object, including: The sampling point data of the first reconstructed object is used to indicate position data of each point of at least one point on a first outer surface of the first reconstructed object, wherein the first outer surface includes at least one outer surface on the first reconstructed object; The first neighbor distance is used to indicate the shortest distance between the first reconstructed object and the first target object, including: The first neighbor distance is used to indicate the shortest distance between a first outer surface on the first target object and a second outer surface on the first reconstructed object, where the second outer surface is an outer surface on the first reconstructed object corresponding to the first outer surface on the first target object.

25. The method according to claim 21, characterized in that The sending the first indication information to the terminal device includes: Receiving posture data corresponding to each target data in a plurality of target data in the target perception data of the terminal device, wherein the plurality of target data correspond one-to-one to a plurality of target objects in the first space; Determine the first target data and the second target data from the plurality of target data, wherein a difference between a posture indicated by the posture data corresponding to the first target data and a posture indicated by the posture data in the third target data among the at least one target data is less than a posture difference threshold, and / or a distance between the position data corresponding to the first target data and the position data in the third target data is less than the first distance threshold, and the third target data corresponds to the first reconstructed object; Sending first indication information to the terminal device, where the first indication information is used to indicate the first target data and the second target data among the multiple target data.

26. The method according to claim 25, characterized in that The first indication information is further used to instruct that the first target data be compressed using the first compression method, and the first indication information is further used to instruct that the second target data be compressed using the second compression method.

27. The method according to claim 17 or 18, characterized in that The first compression method includes: determining the residual coding data of the first target data and the posture data corresponding to the first target data as the first compressed data, and the posture data includes position data and / or posture data.

28. A data processing device, characterized in that: include: Processor and memory; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the data processing device performs the data processing method as described in any one of claims 1 to 16, or any one of claims 17 to 27.

29. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the data processing method as described in any one of claims 1 to 16, or any one of claims 17 to 27.

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