CN117528774A - Positioning method, positioning device, computer equipment and storage medium - Google Patents
Positioning method, positioning device, computer equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The application relates to a positioning method, a positioning device, computer equipment and a storage medium. According to the method, the device side reports the capability information to the network side according to the capability request signaling sent by the network side, so that the network side matches a corresponding positioning model according to the capability information to obtain a target positioning model. The network side or the equipment side adopts the target positioning model to position the equipment side so as to obtain positioning information. The method and the device consider the resource allocation capacity and the positioning precision requirement of the device side, and reduce the calculation cost and the time delay of the network side or the device side while meeting the positioning precision requirement of the device side.
Description
Technical Field
The present disclosure relates to the field of wireless communications technologies, and in particular, to a positioning method, an apparatus, a computer device, and a storage medium.
Background
The high-precision location service is a key support service of the emerging industries such as the industrial Internet, the Internet of things, the Internet of vehicles and the like, and in the future, mass intelligent networking terminals such as industrial robots, unmanned vehicles, intelligent sensors and the like need to provide accurate, real-time and reliable location services.
In recent years, as the research of machine learning theory goes deep, machine learning is widely applied to the field of high-precision positioning by the strong feature extraction capability and the strong nonlinear fitting capability. However, there are still some problems that are difficult to be effectively solved by the conventional signal processing method in this field, such as NLOS identification (Non-Line of Sight), position estimation under NLOS conditions, aoA (Angle of Arrival) estimation under strong multipath environment, and the like. To solve the above problem, the machine learning method generally selects a relatively complex model and a large amount of computing resources to better extract effective information from the large-scale redundant data set, so as to obtain positioning information with higher accuracy. However, the large-scale model has high requirements on deployment resources, on one hand, the memory and the video memory are needed to be large enough to store a large number of parameters of the model, and on the other hand, the calculation power is needed to meet the requirements of calculation delay.
This results in increased computational overhead and latency when model reasoning is used. Especially, in the downlink positioning, if the computing and storage capacities of the equipment side are limited, the problem that the resources are insufficient and the model is difficult to deploy and use easily occurs.
Disclosure of Invention
Based on this, it is necessary to provide a positioning method, an apparatus, a computer device and a storage medium in order to solve the above technical problems.
In a first aspect, the present application provides a positioning method, applied to a network side, where the method includes:
transmitting a capability request signaling to a device side, wherein the capability request signaling is related to positioning capability of the device side;
receiving the reported positioning capability information according to the capability request signaling by the equipment side;
according to the positioning capability information, matching with a pre-stored positioning model to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
In one embodiment, the method is characterized by: the positioning capability information comprises positioning capability type and positioning parameter information, and the configuration parameters comprise at least one of computing capability, storage capability, positioning precision requirement and reasoning time delay requirement;
the step of matching the positioning capability information with a pre-stored positioning model to obtain a target positioning model comprises the following steps:
determining the type of a positioning model according to the type of the positioning capability;
determining the size of a positioning model according to the configuration parameters;
And matching to obtain a corresponding target positioning model according to the type and the size.
In one embodiment, the implementation manner of the target positioning model for positioning the equipment side includes:
the network adopts the target positioning model to position the equipment side;
or the network side provides the target positioning model to the equipment side so that the equipment side adopts the target positioning model to position the equipment side and uploads the obtained position information to the network side.
In one embodiment, the network side provides the object positioning model to the device side, including:
and receiving a model information request of the equipment side, and feeding back the model information of the target positioning model to the equipment side, wherein the model information comprises model parameters and a model structure.
In one embodiment, the method further comprises:
receiving an activation request sent by the equipment side after receiving the target positioning model;
and feeding back an activation signaling corresponding to the activation request to the equipment side, wherein the activation signaling is used for indicating the equipment side to adopt the target positioning model to position the equipment side.
In a second aspect, the present application further provides a positioning method, applied to a device side, where the method includes:
receiving a capability request signaling sent by a network side, wherein the capability request signaling is related to positioning capability of a device side;
reporting positioning capability information to the network side according to the capability request signaling so that the network side can be matched with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
In a third aspect, the present application further provides a positioning method, the method including:
the network side sends a capability request signaling to the equipment side, wherein the capability request signaling is related to the positioning capability of the equipment side;
the equipment side reports positioning capability information to the network side according to the capability request signaling, so that the network side is matched with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
In a fourth aspect, the present application also provides a positioning device, the device comprising:
the network side is used for sending a capacity request signaling to the equipment side, and after receiving positioning capacity information reported by the equipment side, the network side is matched with a pre-stored positioning model according to the positioning capacity information to obtain a target positioning model; wherein the capability request signaling is related to the positioning capability of the equipment side, and the target positioning model is used for positioning the equipment side;
And the equipment side is used for reporting the capability information to the network side according to the capability request signaling.
In a fifth aspect, the present application also provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method of any of the first, second, or third aspects when the computer program is executed.
In a sixth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the method of any of the first, second, or third aspects.
The positioning method, the positioning device, the computer equipment and the storage medium have at least the following advantages:
according to the method, the device side reports the capability information to the network side according to the capability request signaling sent by the network side, so that the network side matches a corresponding positioning model according to the capability information to obtain a target positioning model. The network side or the equipment side adopts the target positioning model to position the equipment side so as to obtain positioning information. The method and the device consider the resource allocation capacity and the positioning precision requirement of the device side, and reduce the calculation cost and the time delay of the network side or the device side while meeting the positioning precision requirement of the device side.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the invention and are not to be construed as limiting the application.
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of an application environment for a positioning method in one embodiment;
FIG. 2 is a flow chart of a positioning method in one embodiment;
fig. 3 is a schematic flow chart of uplink positioning based on NRPPA protocol in one embodiment;
fig. 4 is a schematic flow chart of downlink positioning based on NRPPA protocol in one embodiment;
fig. 5 is a flow chart illustrating downlink positioning based on LPP protocol in one embodiment;
FIG. 6 is a flowchart illustrating a process for obtaining a target positioning model in one embodiment;
FIG. 7 is a flow chart of a positioning method according to another embodiment;
FIG. 8 is a flow chart of a positioning method according to another embodiment;
FIG. 9 is a block diagram of a positioning device in one embodiment;
fig. 10 is an internal structural view of a computer device in one embodiment.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
Some exemplary embodiments of the invention have been described for illustrative purposes, it being understood that the invention may be practiced otherwise than as specifically shown in the accompanying drawings.
The positioning method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the device side 102 communicates with the network side 104 via a wireless network. It should be understood that the network side 104 is disposed on a server, and a data storage system is connected to the network side 104, and the data storage system may store data that needs to be processed by the network side 104. The data storage system may be integrated on a server on the network side 104, or may be located on a cloud or other network server. In addition, a plurality of base stations are arranged between the device side 102 and the network side 104, and are key components of the wireless network and are responsible for providing signal coverage and data transmission.
Wherein the network side 104 may send capability request signaling to the device side 102, the capability request signaling being related to the positioning capability of the device side. The device side 102 responds to the capability request signaling and reports the capability information to the network side 104, so that the network side 104 matches the corresponding positioning model according to the capability information to obtain the target positioning model. In this way, the network side 104 or the device side 102 can locate the device side 102 according to the target location model.
According to the positioning method, the equipment side reports the capability information to the network side according to the capability request signaling sent by the network side, so that the network side matches a corresponding positioning model according to the capability information to obtain a target positioning model. The network side or the equipment side adopts the target positioning model to position the equipment side so as to obtain positioning information. The method and the device consider the resource allocation capacity and the positioning precision requirement of the device side, and reduce the calculation cost and the time delay of the network side or the device side while meeting the positioning precision requirement of the device side.
Referring to fig. 2, in some embodiments, the present application provides a positioning method applied to a network side, which specifically includes the following steps:
Step S202, sending a capability request signaling to the device side.
Step S204, the receiving device side reports the positioning capability information according to the capability request signaling.
Step S206, according to the positioning capability information, matching with a pre-stored positioning model to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
In particular, capability request signaling relates to positioning capabilities on the device side. Generally speaking, the positioning capability of the device side is associated with the resource allocation capability and positioning accuracy requirement thereof, wherein the resource allocation capability is used for representing the configuration of the device side and mainly comprises at least one of the computing capability, the storage capability and the reasoning time delay requirement of the device side; the positioning accuracy requirement is dependent on the resource allocation capability, and is correspondingly higher when the resource allocation capability is higher.
The network side sends the capability request signaling to the equipment side, so that the equipment side can feed back the required positioning capability information according to the capability request signaling, wherein the positioning capability information is used for representing the positioning capability of the equipment side and comprises a plurality of parameters which are used for matching a proper positioning model. Further, the positioning capability information comprises configuration parameters and positioning capability types, wherein the configuration parameters comprise at least one of computing capability, storage capability, reasoning delay requirement and positioning accuracy requirement; the positioning capability type is a type of positioning model used in positioning measurement, and the positioning models may be a calculated non-line of sight (NLOS), angle of Arrival (AoA), time of Arrival (ToA), time difference of Arrival (Time Difference of Arrival, TDoA), or device address.
And the target positioning model is used for positioning the equipment side. It should be understood that, according to different positioning protocols, the network side is preconfigured with multiple positioning models for selection, and the calculation principles of the positioning models are different. For example, the GPS positioning model is based on the principle of triangulation, which is mainly the use of multiple satellite signals to determine the three-dimensional position of the longitude, latitude and altitude of a receiver. Wi-Fi positioning is the use of the location information and signal strength of Wi-Fi hotspots to estimate the location of a device. Illustratively, the new radio positioning protocol NRPPA or the long term evolution positioning protocol LPP is adopted in the present embodiment to position the device side. Wherein, the NRPPA protocol is a protocol between an NR Radio Access Network (RAN) node and a Location Management Function (LMF) in the 3GPP protocol, and is used for information interaction between a next generation base station (gNB) and the LMF, supporting multiple positioning models, where a common positioning model includes: TOA model, TDOA model, AOA model, RSS (Received Signal Strength) model, etc. The LPP protocol is specifically designed for LTE (Long-Term Evolution) networks and provides a variety of positioning models within LTE networks, where common positioning models include: TOA model, TDOA model, AOA model, RSS model, ECID model, OTDOA model, GNSS model, etc.
Optionally, the implementation manner of the target positioning model for positioning the equipment side includes:
the network adopts a target positioning model to position the equipment side;
or the network side provides the target positioning model to the equipment side so that the equipment side adopts the target positioning equipment to position the equipment side and uploads the obtained position information to the network side.
Specifically, in the implementation process of the positioning method, there are two modes of uplink positioning and downlink positioning.
In the uplink positioning mode, after the network side is matched to obtain a target positioning model, the target positioning model is adopted to position the equipment side, and the obtained positioning information is stored. By adopting the scheme, the network side can select a proper positioning model according to the precision requirement of the equipment side, and when the required precision is lower, the positioning precision and time delay requirements are met and model reasoning calculation resources are saved by matching the compressed lightweight positioning model.
For example, referring to fig. 3, in this embodiment of the present application, the signaling flow in uplink positioning of the positioning method of the present application is further described in detail by taking the to-be-positioned device as an AI device, the positioning model as an AI model, and the positioning protocol as NRPPA as an example:
Step S301, the network side performs NRPPa configuration information interaction with each base station. A plurality of base stations are arranged between the network side and the equipment side, and signaling transmission is carried out through each base station.
In step S302, the network side sends a positioning request to the serving base station, requesting UL information required by the device side, where the UL information includes signal quality, signal strength, interference level, and the like.
In step S303, the serving base station sends a capability request signaling to the device side. Wherein the capability request signaling is related to the positioning capability of the device side.
Step S304, the equipment side reports positioning capability information to the service base station according to the capability request signaling, wherein the positioning capability information comprises configuration parameters and positioning capability types, and the configuration parameters comprise at least one of computing capability, storage capability, reasoning time delay requirements and positioning accuracy requirements. Further, the configuration parameters are divided into a plurality of sections in advance according to a preset rule, and the positioning capability information further comprises sections to which the configuration parameters belong, so that the equipment side reports the sections to which the configuration parameters belong to the network side.
In step S305, the serving base station confirms the available resources of the UL-SRS positioning reference signal and uses the resources to configure the target device, for example, determine signal transmission parameters such as frequency, power, etc. of the target device, so that the target device can correctly transmit and receive the UL-SRS signal, thereby performing positioning.
In step S306, the serving base station provides the configuration information of the UL-SRS positioning reference signal to the network side in the NRPPa positioning information response signaling.
In step S307, when the configuration of the SRS is semi-persistent or non-periodic, the network side requests to activate the SRS positioning reference signal on the device side by sending an NRPPa positioning activation request message to the serving base station on the device side. The serving base station then activates SRS transmission at the device side and sends an NRPPa location activation response message. The device side starts transmitting UL-SRS according to the time domain configuration of the UL-SRS positioning reference signal.
Step S308, the network side provides UL information to the selected gNB/TRP in NRPPa measurement request signaling, which includes all information required for the base station to perform UL measurement.
In step S309, the selected base station measures SRS positioning reference signals from the end user.
In step S310a, the selected base station reports measurement information to the network side in an NRPPa measurement response message.
In step S310b, the serving base station reports the AI-positioning capability of the device side to the network side.
Step S311, the network side transmits NRPPa location deactivation signaling to the serving base station.
In the downlink positioning mode, after the network side is matched to obtain a target positioning model, the target positioning model is provided for the equipment side. After the equipment receives the target positioning model, the target positioning equipment is adopted to position the equipment, and the obtained position information is uploaded to the network side. By adopting the scheme, under the condition that the computing capacity and the storage capacity of the equipment side are limited, the matched target positioning model can greatly reduce the resource consumption of the equipment side, and the transmission cost of the model is reduced while the positioning precision and the time delay requirements are met.
For example, please refer to fig. 4, wherein, in order to enable those skilled in the art to fully understand the present application, the following details are given on a signaling flow of the positioning method in downlink positioning by taking a to-be-positioned device as an AI device, a positioning model as an AI model, and a positioning protocol as NRPPA as an example:
in step S401, the network side sends a capability request signaling to the device side. Wherein the capability request signaling is related to the positioning capability of the device side.
In step S402, the device side reports the positioning capability information to the network side according to the capability request signaling. Wherein the positioning capability information includes configuration parameters and positioning capability types, the configuration parameters including at least one of computing capability, storage capability, inference delay requirement, and positioning accuracy requirement. Further, the configuration parameters are divided into a plurality of sections in advance according to a preset rule, and the positioning capability information further comprises sections to which the configuration parameters belong, so that the equipment side reports the sections to which the configuration parameters belong to the network side.
In step S403, the device sends an AI model information request to the network side.
In step S404, the network side responds to the AI model information request, matches the corresponding AI positioning model according to the positioning capability information, obtains a target positioning model, and provides model information of the target positioning model to the device side. The positioning capability type is used for determining the type of the positioning model, and the configuration parameters are used for determining the size of the positioning model. The model information includes model parameters and model structures. If the equipment side is provided with a positioning model with the same structure as the target positioning model, only model parameters need to be fed back to the equipment side; otherwise, both the model parameters and the model structure need to be fed back to the equipment side.
In step S405, after receiving the target positioning model, the device side sends an activation request to the network side.
In step S406, the network side responds to the activation request and feeds back the activation signaling to the device side, and the device side adopts the target positioning model to start positioning itself, and uploads the obtained position information to the network side.
For example, referring to fig. 5, in this embodiment of the present application, the signaling flow of the positioning method in downlink positioning is further described in detail by taking the to-be-positioned device as an AI device, the positioning model as an AI model, and the positioning protocol as an LPP as an example:
in step S501, according to the LPP protocol, the network side sends a capability request signaling to the device side. The capability request signaling includes LPP location capability request signaling and AI capability request signaling. Wherein the LPP positioning capability request is used to indicate a type of positioning model, and the AI capabilities include at least one of computing capability, storage capability, reasoning delay requirement, and positioning accuracy requirement.
S502, according to LPP protocol, the equipment side provides LPP positioning ability to the network side, wherein the LPP positioning ability is the type of positioning ability in the positioning ability information. The equipment side also reports the AI positioning capability to the network side, wherein the AI positioning capability is the configuration parameter in the positioning capability information. Further, the configuration parameters are divided into a plurality of sections in advance according to a preset rule, and the positioning capability information further comprises sections to which the configuration parameters belong, so that the equipment side reports the sections to which the configuration parameters belong to the network side.
S503a, according to the LPP protocol, the device sends an assistance data request to the network side, wherein the assistance data includes ephemeris data, cellular network information, reference signal data for measuring time difference, environment information, network parameters, satellite signal data, and the like.
S503b, the equipment sends an AI model information request to the network side, wherein the AI model information can be a model parameter, a model structure and a model parameter.
S504a, the network side responds to the auxiliary data request, and sends auxiliary data corresponding to the auxiliary data request to the device side.
S504b, the network side responds to the AI model information request, matches the corresponding AI positioning model according to the positioning capability information to obtain a target positioning model, and provides the model information of the target positioning model to the equipment side. The positioning capability type is used for determining the type of the positioning model, and the configuration parameters are used for determining the size of the positioning model. The model information includes model parameters and model structures. If the equipment side is provided with a positioning model with the same structure as the target positioning model, only model parameters need to be fed back to the equipment side; otherwise, both the model parameters and the model structure need to be fed back to the equipment side.
S505, after receiving the target positioning model, the equipment side sends an activation request to the network side.
And S506, the network side responds to the activation request and feeds back activation signaling to the equipment side.
S507, the network side requests location information to the device side.
S508, the equipment side adopts a target positioning model to carry out DL-PRS measurement.
S509, according to the LPP protocol, the device sends providing location information signaling to the network side to deliver location information to the network side.
Referring to fig. 6, optionally, according to the positioning capability information, the network side matches with a pre-stored positioning model to obtain a target positioning model, including:
step S602, determining the type of the positioning model according to the type of the positioning capability.
The positioning capability type can be divided according to positioning signals corresponding to various positioning precision requirements.
For example, the positioning accuracy requirement may indicate a positioning accuracy requirement of an angle of Arrival (AoA), may indicate a positioning accuracy requirement of a Time difference of Arrival (Time Difference of Arrival, TDoA), may indicate a positioning accuracy requirement of a Time of Arrival (ToA), and may indicate a positioning accuracy requirement of a non line of sight (NLOS).
In some embodiments, the type of the positioning model corresponding to the positioning accuracy requirement may be determined according to the positioning signal corresponding to the positioning accuracy requirement. For example, if the positioning capability received by the network side is the positioning accuracy requirement of the AoA, the type of the positioning model may be a corresponding positioning model of the AoA; if the positioning capability received by the network side is the positioning accuracy requirement of the TDoA, the type of the positioning model can be a corresponding positioning model of the TDoA; if the positioning capability received by the network side is the positioning accuracy requirement of the ToA, the type of the positioning model can be correspondingly the positioning model of the ToA.
In some embodiments, a positioning model may simultaneously correspond to multiple positioning accuracy requirements, and accordingly, when the received positioning capability includes multiple positioning accuracy requirements corresponding to the positioning model, the positioning model may be used. Illustratively, an observable time difference of arrival (Observed Time Difference of Arrival, OTDOA) positioning model uses mainly two positioning signals, toA and TDoA, when positioning, and measures the time difference of arrival of signals from different base stations to estimate the position. At the same time, NLOS conditions may also affect the accuracy of OTDOA positioning. Thus, the OTDOA positioning model corresponds to three positioning accuracy requirements of ToA, TDoA and NLOS simultaneously. When the network side receives the three positioning accuracy requirements including ToA, TDoA and NLOS, the OTDOA positioning model can be determined to be adopted.
Step S604, determining the size of the positioning model according to the configuration parameters.
Wherein the size of the positioning model is used to characterize the compression degree of the positioning model, a larger positioning model may be, for example, an uncompressed original training model, and a smaller positioning model may be, for example, a lightweight model after model compression. Illustratively, the OTDOA positioning model may include both the original OTDOA positioning model and the compressed OTDOA positioning model.
The configuration parameters comprise computing capacity and storage capacity of the terminal side, and positioning accuracy requirements and reasoning time delay requirements indicated by the positioning capacity.
For example, if the configuration of the equipment side is higher, the equipment side has good computing capability and storage capability, and the requirements on reasoning time delay and positioning accuracy are higher, an original training model can be selected as a positioning model; otherwise, the compressed lightweight model can be selected as a positioning model.
It should be appreciated that the size of either the original training model or the compressed lightweight model is fixed. Therefore, in some embodiments, the configuration parameter uploaded at the device side does not need to be very accurate, and may be divided into a plurality of intervals, and the interval to which the configuration parameter belongs may be provided during configuration. The equipment side can also determine the interval to which the configuration parameter belongs according to a preset rule, and send the interval to which the configuration parameter belongs to the network side, and then the network side matches the size of the positioning model from the pre-stored positioning models according to the interval.
For example, if any configuration parameter is within a section corresponding to the compressed lightweight model, the compressed lightweight model may be selected. If all the configuration parameters are in the interval of the original training model, the original training model can be selected.
In other embodiments, to improve the matching rate, under the condition of low positioning accuracy requirement, the configuration parameters may be divided into three levels, namely, low, medium and high, and the corresponding level of the configuration parameters is provided during configuration. Accordingly, the network side may determine the size of the positioning model based on the level to which the configuration parameter belongs.
Step S606, matching to obtain a corresponding target positioning model according to the type and the size.
In some embodiments, the type of the appropriate positioning model can be matched by the category, and the size of the model can determine whether to use the original training model or the compressed lightweight model, so that the target positioning model can be obtained by matching.
For example, if the network side receives a request for positioning accuracy including three types of ToA, TDoA and NLOS, it may be determined to use the OTDOA positioning model. Meanwhile, the configuration of the equipment side is higher, the calculation capability and the storage capability are good, and the inference delay requirement and the positioning accuracy requirement are higher, so that the size of the model can be determined as an original training model. At this time, the network side may determine that the target positioning model corresponding to the matching is the OTDOA positioning model originally trained.
In the above embodiment, the type of the model is determined by the positioning capability type, the size of the model is determined by the configuration parameters, and finally, a proper positioning model is matched according to the determined type and size, so that the resource consumption of the equipment side is greatly reduced, and the transmission overhead of the model is reduced while the positioning precision and time delay requirements are met.
Optionally, the network side provides the target positioning model obtained by matching to the device side, including:
and receiving a model information request of the equipment side, and feeding back model information of the target positioning model to the equipment side, wherein the model information comprises model parameters and a model structure. The model parameters are parameters such as weight, deviation and the like learned by the positioning model in the training process, and are used for describing and positioning specific characteristics and attributes of the defined model. The model structure refers to the overall architecture of the model, e.g., the model structure of the positioning model may include input and output layers, hidden layers, activation functions, etc.
Specifically, if the device side has installed a positioning model having the same structure as the target positioning model, then the network side only needs to send the model parameters to the device side. If the equipment side does not install the positioning model, the model parameters and the structure of the positioning model are required to be sent to the equipment side. Further, the model information may also include data about the surrounding environment, such as base station location, signal strength, multipath propagation, etc. These data are very important to adapt to different environmental conditions. The equipment side can adapt to different environments according to the data so as to improve the reliability of positioning. Further, the model parameters may include data about base stations, satellites, or other positioning reference points, in addition to parameters such as weights and biases learned by the positioning model during training. These data can be used to improve the processing and correction of the positioning measurement data, thereby improving the accuracy of the positioning.
Optionally, in some embodiments, the positioning method provided in the embodiments of the present application further includes:
after receiving the target positioning model, the receiving equipment side sends an activation request; and feeding back an activation signaling corresponding to the activation request to the equipment side. The activation signaling is used for indicating the equipment side to adopt a target positioning model to position the equipment side and feeding back positioning information to the network side.
According to the positioning method, according to the positioning capability information fed back by the equipment side, a proper positioning model is matched from the pre-stored positioning models, so that a target positioning model is obtained, and the target positioning model is used for positioning the equipment side. By adopting the scheme, the network side can select a proper positioning model according to the precision requirement of the equipment side, and when the required precision is lower, the positioning precision and time delay requirements are met and model reasoning calculation resources are saved by matching the compressed lightweight positioning model. Meanwhile, under the condition that the computing capacity and the storage capacity of the equipment side are limited, the matched target positioning model can greatly reduce the resource consumption of the equipment side, and the transmission cost of the model is reduced while the positioning precision and the time delay requirements are met.
Referring to fig. 7, in some embodiments, the present application further provides a positioning method, where the positioning method is applied to a device side, and specifically includes the following steps:
step S702, receiving a capability request signaling sent by a network side. Wherein the capability request signaling is related to the positioning capability of the device side.
Step S704, reporting positioning capability information to a network side according to the capability request signaling, so that the network side matches a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
Optionally, the implementation manner of the target positioning model for positioning the equipment side includes:
the network adopts a target positioning model to position the equipment side;
or the network side provides the target positioning model to the equipment side so that the equipment side adopts the target positioning equipment to position the equipment side and uploads the obtained position information to the network side.
Optionally, when the implementation manner of the target positioning model for positioning the device side uses the network side to provide the target positioning model to the device side, the positioning method provided in the embodiment of the present application further includes:
And sending a model information request to a network side, and receiving model information of a target positioning model corresponding to the model information request. Wherein the model information includes model parameters and model structures.
Optionally, the positioning method provided in the embodiment of the present application further includes:
after receiving a target positioning model sent by a network side, sending an activation request to the network side; and when the activation request is received, a target positioning model is adopted to position the self-body.
According to the positioning method, the positioning capability information is sent to the network side, so that the network side can be matched with a proper positioning model from the pre-stored positioning models according to the positioning capability information to obtain a target positioning model, and the target positioning model is used for positioning the equipment side. By adopting the scheme, under the condition that the computing capacity and the storage capacity of the equipment side are limited, the matched target positioning model can greatly reduce the resource consumption of the equipment side, and the transmission cost of the model is reduced while the positioning precision and the time delay requirements are met. Meanwhile, the network side can select a proper positioning model according to the precision requirement of the equipment side, when the required precision is low, the positioning precision and time delay requirements are met by matching the compressed lightweight positioning model, and meanwhile model reasoning calculation resources are saved.
Referring to fig. 8, in some embodiments, the present application further provides a positioning method, where the method includes:
in step S802, the network side sends a capability request signaling to the device side, where the capability request signaling is related to the positioning capability of the device side.
Step S804, the equipment side reports positioning capability information to the network side according to the capability request signaling, so that the network side matches a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
Optionally, the implementation manner of the target positioning model for positioning the equipment side includes:
the network adopts a target positioning model to position the equipment side;
or the network side provides the target positioning model to the equipment side so that the equipment side adopts the target positioning equipment to position the equipment side and uploads the obtained position information to the network side.
Optionally, the network side matches with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model, which comprises the following steps: determining the type of the positioning model according to the type of the positioning capability; determining the size of a positioning model according to the configuration parameters; and matching to obtain a corresponding target positioning model according to the type and the size.
Optionally, the configuration parameters are divided into a plurality of intervals in advance according to a preset rule, and the capability information further includes intervals to which the configuration parameters belong, and at this time, the network side determines the size of the positioning model according to the configuration parameters, including: determining a section to which the configuration parameter belongs according to the configuration parameter; and determining the size of the positioning model according to the interval.
Optionally, the network side provides the target positioning model obtained by matching to the device side, including:
and receiving a model information request of the equipment side, and feeding back model information of the target positioning model to the equipment side, wherein the model information comprises model parameters and a model structure.
Optionally, the positioning method of the embodiment of the present application further includes:
and the equipment side sends an activation request to the network side after receiving the target positioning model. The network side responds to the activation request and feeds back an activation signaling corresponding to the activation request to the equipment side, and the equipment side adopts a target positioning model to position the equipment side after receiving the activation signaling.
According to the positioning method, the network side is matched with the pre-stored positioning model according to the positioning capability information fed back by the equipment side, and the target positioning model is obtained. The network side or the equipment side can locate the equipment side according to the target location model. By adopting the scheme, when the equipment side adopts the target positioning model for positioning, under the condition that the computing capacity and the storage capacity of the equipment side are limited, the matched target positioning model can greatly reduce the resource consumption of the equipment side, and the transmission cost of the model is reduced while the positioning precision and the time delay requirements are met. When the network side adopts the target positioning model to perform positioning, the network side can select a proper positioning model according to the precision requirement of the equipment side, and when the required precision is lower, the positioning precision and the time delay requirement are met and model reasoning calculation resources are saved by matching the compressed lightweight positioning model.
Based on the same inventive concept, the embodiment of the application also provides a positioning device for realizing the positioning method. The implementation of the solution provided by the device is similar to that described in the above method, so the specific limitations in one or more embodiments of the positioning device provided below may be referred to above for limitations of the positioning method, which are not repeated here.
Referring to fig. 9, in some embodiments, a positioning device is provided in an embodiment of the present application, including: network side and equipment side.
The network side is used for sending the capability request signaling to the equipment side, and after receiving the positioning capability information reported by the equipment side, the network side is matched with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model. Wherein the capability request signaling is related to the positioning capability of the device side, and the target positioning model is used for positioning the device side.
And the equipment side is used for reporting the capability information to the network side according to the capability request signaling.
Optionally, the network side is further configured to locate the device side by using the target location model;
or the network side is also used for providing the target positioning model to the equipment side so that the equipment side adopts the target positioning equipment to position the equipment side and upload the obtained position information to the network side.
Optionally, the network side matches with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model, which comprises the following steps: determining the type of the positioning model according to the type of the positioning capability; determining the size of a positioning model according to the configuration parameters; and matching to obtain a corresponding target positioning model according to the type and the size.
Optionally, in order to improve the matching rate, in the case of low positioning accuracy requirement, the device side may divide the configuration parameter into a plurality of intervals according to a preset rule, and send the interval to which the configuration parameter belongs to the network side, where the network side matches the size of the positioning model from the pre-stored positioning models according to the interval.
Optionally, the network side provides the target positioning model obtained by matching to the device side, including: and receiving a model information request of the equipment side, and feeding back model information of the target positioning model to the equipment side, wherein the model information comprises model parameters and a model structure.
Optionally, the device side is further configured to send an activation request to the network side after receiving the target positioning model. And after receiving the activation signaling corresponding to the activation request, adopting a target positioning model to position the target positioning model, and feeding back positioning information to the network side. The network side is further configured to respond to the activation request, and feed back an activation signaling corresponding to the activation request to the device side.
According to the positioning device, the network side is matched with a pre-stored positioning model according to the positioning capability information fed back by the equipment side, and a target positioning model is obtained. The network side or the equipment side can locate the equipment side according to the target location model. By adopting the scheme, when the equipment side adopts the target positioning model for positioning, under the condition that the computing capacity and the storage capacity of the equipment side are limited, the matched target positioning model can greatly reduce the resource consumption of the equipment side, and the transmission cost of the model is reduced while the positioning precision and the time delay requirements are met. When the network side adopts the target positioning model to perform positioning, the network side can select a proper positioning model according to the precision requirement of the equipment side, and when the required precision is lower, the positioning precision and the time delay requirement are met and model reasoning calculation resources are saved by matching the compressed lightweight positioning model.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
The various modules in the positioning device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In some embodiments, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 10. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a positioning method. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 10 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In some embodiments, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, which processor, when executing the computer program, implements the method steps of the positioning method provided in the above embodiments.
In some embodiments, a computer readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, implements the method steps of the positioning method provided in the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A positioning method, applied to a network side, the method comprising:
transmitting a capability request signaling to a device side, wherein the capability request signaling is related to positioning capability of the device side;
receiving the reported positioning capability information according to the capability request signaling by the equipment side;
according to the positioning capability information, matching with a pre-stored positioning model to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
2. The method according to claim 1, characterized in that: the positioning capability information comprises positioning capability type and positioning parameter information, and the configuration parameters comprise at least one of computing capability, storage capability, positioning precision requirement and reasoning time delay requirement;
the step of matching the positioning capability information with a pre-stored positioning model to obtain a target positioning model comprises the following steps:
determining the type of a positioning model according to the type of the positioning capability;
determining the size of a positioning model according to the configuration parameters;
and matching to obtain a corresponding target positioning model according to the type and the size.
3. The method of claim 1, wherein the implementation of the object location model for locating the device side comprises:
the network adopts the target positioning model to position the equipment side;
or the network side provides the target positioning model to the equipment side so that the equipment side adopts the target positioning model to position the equipment side and uploads the obtained position information to the network side.
4. A method according to claim 3, wherein the network side providing the object location model to the device side comprises:
And receiving a model information request of the equipment side, and feeding back the model information of the target positioning model to the equipment side, wherein the model information comprises model parameters and a model structure.
5. A method according to claim 3, characterized in that the method further comprises:
receiving an activation request sent by the equipment side after receiving the target positioning model;
and feeding back an activation signaling corresponding to the activation request to the equipment side, wherein the activation signaling is used for indicating the equipment side to adopt the target positioning model to position the equipment side.
6. A positioning method, applied to a device side, the method comprising:
receiving a capability request signaling sent by a network side, wherein the capability request signaling is related to positioning capability of a device side;
reporting positioning capability information to the network side according to the capability request signaling so that the network side can be matched with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
7. A method of positioning, the method comprising:
The network side sends a capability request signaling to the equipment side, wherein the capability request signaling is related to the positioning capability of the equipment side;
the equipment side reports positioning capability information to the network side according to the capability request signaling, so that the network side is matched with a pre-stored positioning model according to the positioning capability information to obtain a target positioning model; the target positioning model is used for positioning the equipment side.
8. A positioning device, the device comprising:
the network side is used for sending a capacity request signaling to the equipment side, and after receiving positioning capacity information reported by the equipment side, the network side is matched with a pre-stored positioning model according to the positioning capacity information to obtain a target positioning model; wherein the capability request signaling is related to the positioning capability of the equipment side, and the target positioning model is used for positioning the equipment side;
and the equipment side is used for reporting the capability information to the network side according to the capability request signaling.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-7.
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| CN202311777243.1A CN117528774A (en) | 2023-12-21 | 2023-12-21 | Positioning method, positioning device, computer equipment and storage medium |
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| CN202311777243.1A CN117528774A (en) | 2023-12-21 | 2023-12-21 | Positioning method, positioning device, computer equipment and storage medium |
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| CN202311777243.1A Pending CN117528774A (en) | 2023-12-21 | 2023-12-21 | Positioning method, positioning device, computer equipment and storage medium |
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