Communication environment determination method, data processing device, vehicle and storage medium

Abstract

The present invention relates to a communication environment determination method based on ultra-wideband, a data processing device, a vehicle and a storage medium for determining the type of communication environment. The method comprises: A. determining a channel impulse response in a current ultra-wideband communication process based on a received ultra-wideband signal; B. calculating a channel time dispersion parameter based on the channel impulse response; and C. inputting the channel time dispersion parameter into an algorithm model, and generating first determination information indicating the type of the current communication environment based on the algorithm model.

Description

Technical Field

[0001] The present invention relates to the technical field of ultra-wideband, and more particularly to a communication environment determination method based on ultra-wideband, a data processing device for determining the type of communication environment, a vehicle and a storage medium. Background Art

[0002] At present, many application scenarios require the determination of the type of environment (such as indoors or outdoors) in which the device is located. Some existing technologies use smartphones to detect the number of surrounding base stations, and judge whether the phone is located indoors or outdoors based on the assumption that the number of base stations detected outdoors is greater than that detected indoors. Since modern system communication systems widely use micro-cell and micro-micro-cell technology for networking, the above assumption is not always valid. In addition, some existing technologies use information provided by multiple sensors (such as road signs, magnetic field strength, road texture, temperature, light intensity, odor, pollutant detection, etc.) to comprehensively determine the type of environment. Since this method requires the use of technologies such as visual recognition, the system is complex and costly.

[0003] In view of this, it is necessary to propose an improved communication environment determination method. Summary of the invention

[0004] Embodiments of the present application provide an improved communication environment determination method, a data processing device, a vehicle, and a storage medium for performing channel detection using ultra-wideband technology and determining the type of communication environment based on the channel detection results.

[0005] According to one aspect of the present invention, a method for determining a communication environment based on ultra-wideband is provided, comprising the following steps: A. determining a channel impulse response in a current ultra-wideband communication process based on a received ultra-wideband signal; B. calculating a channel time dispersion parameter based on the channel impulse response; and C. inputting the channel time dispersion parameter into an algorithm model, and generating first judgment information indicating the type of the current communication environment based on the algorithm model.

[0006] As an alternative or supplement to the above solution, the method according to an embodiment of the present invention further includes: D. determining positioning model parameters for the current communication environment type based on the first judgment information.

[0007] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the channel time dispersion parameters include one or more of the following items: the number of multipaths, the amplitude and delay of each multipath component, the average excess delay, the mean square delay spread and the maximum multipath delay.

[0008] As an alternative or supplement to the above scheme, in a method according to one embodiment of the present invention, the algorithm model includes a machine learning model, which is constructed based on a training data set containing channel time dispersion parameter samples and labeled information characterizing the communication environment type corresponding to the samples.

[0009] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the algorithm model includes a threshold classification model, and step C includes: C1, obtaining the line-of-sight type of the current ultra-wideband communication, wherein the line-of-sight type includes line-of-sight propagation and non-line-of-sight propagation; C2, determining a dispersion parameter threshold corresponding to the line-of-sight type; C3, comparing the channel time dispersion parameter with the dispersion parameter threshold; and C4, determining the current communication environment type based on the comparison result.

[0010] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the thresholds of the average excess delay and the mean square delay spread for non-line-of-sight propagation are respectively greater than the thresholds of the average excess delay and the mean square delay spread for line-of-sight propagation.

[0011] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, the current communication environment type includes indoor and outdoor.

[0012] According to another aspect of the present invention, there is provided a data processing device for determining the type of communication environment, comprising: a memory; a processor; and a computer program stored in the memory and executable on the processor, wherein the execution of the computer program causes the following steps to be performed: A. determining a channel impulse response in a current ultra-wideband communication process based on a received ultra-wideband signal; B. calculating a channel time dispersion parameter based on the channel impulse response; and C. inputting the channel time dispersion parameter into an algorithm model, and generating first judgment information indicating the type of the current communication environment based on the algorithm model.

[0013] As an alternative or supplement to the above solution, in an apparatus according to an embodiment of the present invention, the execution of the computer program further causes the following steps to be executed: D. determining positioning model parameters for the current communication environment type based on the first judgment information.

[0014] As an alternative or supplement to the above scheme, in an apparatus according to an embodiment of the present invention, the algorithm model includes a threshold classification model, and the operation of the computer program causes step C to be executed in the following manner: C1, obtaining the line-of-sight type of the current ultra-wideband communication, wherein the line-of-sight type includes line-of-sight propagation and non-line-of-sight propagation; C2, determining a dispersion parameter threshold corresponding to the line-of-sight type; C3, comparing the channel time dispersion parameter with the dispersion parameter threshold; and C4, determining the current communication environment type based on the comparison result.

[0015] As an alternative or supplement to the above scheme, in a device according to an embodiment of the present invention, the thresholds of the average excess delay and the mean square delay spread for non-line-of-sight propagation are respectively greater than the thresholds of the average excess delay and the mean square delay spread for line-of-sight propagation.

[0016] According to another aspect of the present invention, there is provided a vehicle, comprising: an ultra-wideband transmitter; an ultra-wideband receiver for detecting an ultra-wideband signal emitted by the ultra-wideband transmitter; and any one of the data processing devices described above.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, any one of the methods described above is implemented.

[0018] Firstly, the communication environment determination scheme proposed in the present invention can utilize ultra-wideband technology for channel detection. Since ultra-wideband signals use narrow pulses with extremely short duration, their time and space resolution are very strong, so they have extremely high multipath resolution, which can improve the accuracy of channel detection while obtaining strong anti-fading capability.

[0019] Secondly, the communication environment determination scheme proposed in the present invention cleverly utilizes the time dispersion characteristics of the multipath effect, and further determines the communication environment type with the help of an algorithm model constructed based on prior knowledge of channel time dispersion parameters (for example, the average excess delay and mean square delay spread of non-line-of-sight propagation are greater than those of line-of-sight propagation, the average excess delay and mean square delay spread of the outdoor environment are greater than those of the indoor environment, the number of multipaths in the outdoor environment is less than that in the indoor environment, etc.), thereby effectively improving the efficiency and accuracy of environment determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and / or other aspects and advantages of the present invention will become clearer and easier to understand through the following description in conjunction with the accompanying drawings, in which the same or similar elements are represented by the same reference numerals.

[0021] The accompanying drawings include:

[0022] Figure 1is a schematic flow chart of a communication environment determination method 10 according to an embodiment of the present invention;

[0023] Figure 2 is a schematic block diagram of a data processing device 20 for determining a type of a communication environment according to an embodiment of the present invention; and

[0024] Figure 3 FIG. 2 is a schematic block diagram of a vehicle 30 according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In this specification, the present invention is more fully described with reference to the accompanying drawings in which exemplary embodiments of the present invention are illustrated. However, the present invention may be implemented in different forms and should not be construed as being limited to the embodiments given herein. The embodiments given are intended to make the disclosure herein comprehensive and complete, so as to more fully convey the scope of the present invention to those skilled in the art.

[0026] It should be noted that the terms "first", "second", etc. in this document are used to distinguish similar objects, and are not necessarily used to describe the order of objects in terms of time, space, size, etc. In addition, unless otherwise specifically stated, the terms "including", "having" and similar expressions in this document are intended to indicate non-exclusive inclusion.

[0027] In this specification, the term "vehicle" or other similar terms include general motor vehicles, such as passenger cars (including sports utility vehicles, buses, trucks, etc.), various commercial vehicles, etc., and include hybrid electric vehicles, electric vehicles, plug-in hybrid electric vehicles, etc. A hybrid electric vehicle is a vehicle with two or more power sources, such as gasoline-powered and electric vehicles.

[0028] Currently, many application scenarios require the determination of the type of environment (such as indoors or outdoors) in which the device is located. For example, mobile phones need to flexibly enable and disable the WiFi scanning function based on the determination of whether it is outdoor or indoor, so as to improve network signals while reducing communication charges; the autonomous driving system needs to select different positioning information based on the determination of the type of environment (for example, if the vehicle is detected to be driving outdoors, the output information of the global positioning system (GPS) and the inertial measurement unit (IMU) is integrated; if it is in an indoor parking lot, the output information of the ultra-wideband (UWB) and the IMU is integrated) to ensure reliable positioning output; the mobile phone needs to report the type of environment it is in so that the operator can accurately determine the coverage range of the base station signal.

[0029] It should be noted that for systems that implement positioning functions based on wireless signal strength (e.g., WiFi and Bluetooth), the received signal strength is not only related to the distance between signal transceivers, but also to the density of reflectors and scatterers in the surrounding environment. Since the indoor wireless communication system operates in an environment with a large number of multipath components, the received signal strength is significantly different from that outdoors under the condition that the distance between signal transceivers is the same. In this case, if the positioning model parameters established according to the outdoor propagation environment are used for indoor positioning, a large error will be introduced, and vice versa. Therefore, if the positioning conditions include a variety of different environmental scenarios, it is necessary to first determine the type of environment in which the current system is located in order to select positioning model parameters specific to the type of environment, thereby improving the positioning accuracy of such systems.

[0030] It should be understood that the communication environment determination scheme proposed in the present invention can be applied to any scenario where the environment type needs to be determined, including but not limited to the above exemplary scenarios. It should also be understood that the communication environment determination scheme proposed in the present invention is implemented based on ultra-wideband technology, so it is required that the device itself has ultra-wideband communication capabilities (for example, equipped with an ultra-wideband transceiver), or has the ability to detect or process ultra-wideband signals.

[0031] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

[0032] Reference now Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of a communication environment determination method 10 according to an embodiment of the present invention.

[0033] In step S110, based on the received ultra-wideband signal, the channel impulse response in the current ultra-wideband communication process is determined. Optionally, the acquisition of the channel impulse response (CIR) can be based on a measurement method known in the art, including but not limited to using a UWB chip or a UWB sniffer with a CIR capture function, and the present invention does not make specific restrictions on this.

[0034] Exemplarily, assuming that the transmitted ultra-wideband signal is s(t), in a multipath propagation environment and without considering noise, the received ultra-wideband signal r(t) can be expressed as:

[0035] r(t)=s(t)*h(t) (Formula 1)

[0036] Among them, h(t) is the channel impulse response in the current ultra-wideband communication process. The channel impulse response h(t) contains the multipath information of the current channel and can be expressed as:

[0037]

[0038] Here, δ(t) is the Dirac function, K is the number of multipaths, and a n is the gain factor (i.e., amplitude) of the nth multipath component, τ n is the arrival delay of the nth multipath component relative to the first multipath component.

[0039] In step S120, based on the channel impulse response, the channel time dispersion parameter is calculated. Exemplarily, the channel time dispersion parameter includes one or more of the following items: the number of multipaths, the amplitude and delay of each multipath component, the average excess delay, the mean square delay spread and the maximum multipath delay.

[0040] Optionally, the time dispersion parameter of the multipath channel in the channel impulse response h(t) is extracted using signal processing technology. For example, the number K of multipaths in h(t), the amplitude a of each multipath component, and n and time delay τ n , and based on K, a n , τ n Calculate the average excess delay, mean square delay spread, and maximum multipath delay.

[0041] The average excess delay τ of a multipath channel mean and mean square delay spread τ rms They are the square roots of the first-order moment and the second-order moment of the channel impulse response, respectively. The specific calculation formula is as follows:

[0042]

[0043]

[0044] in,

[0045] In step S130, the channel time dispersion parameter is input into the algorithm model, and first judgment information indicating the type of the current communication environment is generated based on the algorithm model.

[0046] Exemplarily, the current communication environment type includes indoor and outdoor. In order to more specifically describe the environment in which the device is located, the environment type can be further divided into outdoor open space, outdoor semi-open space, light indoor space (for example, with open doors and windows), deep indoor space (indoor without windows), etc.

[0047] The algorithm model in step S130 is built based on the prior knowledge of the channel time dispersion parameter. For example, the number of reflectors in different types of communication environments (e.g., indoors and outdoors) is different. There are a large number of reflectors in the indoor environment (such as walls, ceilings, floors, furniture, objects, etc.), which causes the ultra-wideband signal to be reflected multiple times in the indoor space, and a large number of signals reach the receiver along multiple reflection paths. Therefore, the number of multipaths in the indoor environment is often greater than that in the outdoor environment. Secondly, for the outdoor environment, the reflected and scattered signals usually need to travel a longer path to reach the receiver, resulting in an average excess delay and mean square delay spread greater than that in the indoor environment. Furthermore, the above-mentioned channel time dispersion parameter is also related to the line-of-sight type of the current ultra-wideband communication, wherein the line-of-sight type includes line-of-sight (LOS) propagation and non-line-of-sight (NLOS) propagation, which depends on the actual arrangement between the ultra-wideband transceivers on the equipment in the specific application. Generally, the average excess delay and mean square delay spread of NLOS propagation are greater than those of LOS propagation.

[0048] Exemplarily, different algorithm models can be built in advance based on the above-mentioned prior knowledge, including but not limited to threshold classification models and machine learning models.

[0049] If a threshold classification model is adopted, the current communication environment type can be determined based on the following steps S131-S134.

[0050] In step S131, the line-of-sight type of the current ultra-wideband communication is obtained. As described above, the line-of-sight type of the ultra-wideband communication depends on the actual arrangement between the ultra-wideband transceivers, so the line-of-sight type can be pre-stored in the data processing device as known information.

[0051] In step S132, the dispersion parameter threshold corresponding to the line-of-sight type is determined. Based on the above prior knowledge, it can be known that the thresholds of the average excess delay and mean square delay spread for non-line-of-sight propagation are respectively greater than the thresholds of the average excess delay and mean square delay spread for line-of-sight propagation. For example, the average excess delay τ of NLOS propagation is mean The threshold is 32ns and the mean square delay spread τ rms The average excess delay of LOS propagation is 21ns. mean The threshold is 21ns and the mean square delay spread τ rms It is 18ns.

[0052] It should be noted that the numerical range of the preset value (eg, dispersion parameter threshold, etc.) described in this document can be set according to actual needs and is not limited to the numerical range shown in this embodiment.

[0053] In step S133, the channel time dispersion parameter is compared with the dispersion parameter threshold. Optionally, the comparison may be for the average excess delay τmean , mean square delay spread τ rms , the number of multipaths K, and the maximum multipath delay.

[0054] In step S134, the current communication environment type is determined based on the above comparison result.

[0055] For example, for NLOS propagation, if the average excess delay τ mean Greater than a first threshold (e.g., 32 ns), mean square delay spread τ rms If the mean square delay spread τ is greater than the second threshold (e.g., 21 ns), the number of multipaths K is less than the third threshold, and the maximum multipath delay is greater than the fourth threshold, then the current communication environment type can be determined to be outdoor, otherwise it is indoor. For example, for LOS propagation, if the mean square delay spread τ rms If the value of the multipath delay is greater than the fifth threshold (for example, 18 ns), the number of multipaths K is less than the sixth threshold, and the maximum multipath delay is greater than the seventh threshold, then the current communication environment type can be determined to be outdoor, otherwise it is indoor.

[0056] Optionally, the algorithm model in step S130 may be a machine learning model, which is constructed based on a training data set including channel time dispersion parameter samples and annotation information characterizing the communication environment type corresponding to the samples. Exemplarily, firstly, a channel time dispersion parameter data set (e.g., average excess delay τ ) obtained in advance is used to obtain a training data set. mean , mean square delay spread τ rms , the number of multipaths K, the maximum multipath delay, one or more of the line-of-sight type) as training samples, and label them with communication environment type labels (for example, indoor or outdoor), so as to obtain a classification model through training. Exemplarily, the classification algorithms used by the model include but are not limited to multilayer perceptron, decision tree, support vector machine, nearest neighbor algorithm, and naive Bayes method. Exemplarily, the output layer of the machine learning model can directly output "1" or "0" to indicate that the current communication environment type is outdoor or indoor.

[0057] Optionally, in step S140, positioning model parameters for the current communication environment type are determined based on the first judgment information.

[0058] As described above, for systems that implement positioning functions based on wireless signal strength (e.g., WiFi and Bluetooth), it is necessary to select positioning model parameters specific to the type of environment the current system is in, so as to improve the positioning accuracy of such systems. Exemplarily, the positioning model may be a positioning model for a keyless entry and start system (PEPS).

[0059] Continue to refer Figure 2 , Figure 2FIG. 2 is a schematic block diagram of a data processing device 20 for determining a type of a communication environment according to an embodiment of the present invention. Figure 2 The device 20 shown can be used to implement Figure 1 The method shown in .

[0060] like Figure 2 As shown, the data processing device 20 includes a communication unit 210, a memory 220 (e.g., a non-volatile memory such as a flash memory, a ROM, a hard disk drive, a magnetic disk, an optical disk, etc.), a processor 230 (e.g., a microprocessor, a microcontroller, etc.), and a computer program 240 stored in the memory 220 and executable on the processor 230.

[0061] The communication unit 210 serves as a communication interface and is configured to establish a communication connection between the apparatus and an external device or network (eg, a UWB transceiver).

[0062] The memory 220 stores a computer program 240 executable by the processor 230. The processor 230 is configured to execute the computer program 240 to implement a corresponding communication environment determination process. The communication environment determination process has been described in detail above and will not be repeated here.

[0063] Figure 3 FIG. 3 is a schematic block diagram of a vehicle 30 according to an embodiment of the present invention. Figure 3 As shown, the vehicle 30 includes an ultra-wideband transmitter 310, an ultra-wideband receiver 320, and a data processing device 330, wherein the data processing device 330 can be used to implement Figure 1 The method shown in .

[0064] The UWB transmitter 310 and the UWB receiver 320 have the capability of transmitting and receiving UWB communication signals, respectively. Exemplarily, the UWB transmitter 310 and the UWB receiver 320 may include a plurality of UWB transceivers and / or a plurality of UWB antennas arranged in an array.

[0065] Optionally, the ultra-wideband transmitter 310 and the ultra-wideband receiver 320 can be arranged to have a line-of-sight path or a non-line-of-sight path. Exemplarily, the ultra-wideband transmitter 310 and the ultra-wideband receiver 320 can be symmetrically installed on the outside of the B-pillars on both sides of the vehicle. Exemplarily, the ultra-wideband transmitter 310 and the ultra-wideband receiver 320 can also be installed at the left front and left rear of the vehicle, respectively. In other embodiments, the ultra-wideband transmitter 310 and the ultra-wideband receiver 320 can be a line-of-sight path, that is, there is no obstruction between them.

[0066] According to another aspect of the present invention, there is also provided a computer readable storage medium storing a computer program, which, when executed by a processor, implements the following Figure 1The computer-readable storage medium may include a random access memory (RAM) such as a synchronous dynamic random access memory (SDRAM), a read-only memory (ROM), a non-volatile random access memory (NVRAM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, other known storage media, etc.

[0067] According to some embodiments of the present invention, ultra-wideband technology can be used for channel detection. Since ultra-wideband signals use narrow pulses with extremely short durations, they have strong time and space resolution and therefore have extremely high multipath resolution, which can improve the accuracy of channel detection while obtaining strong anti-fading capabilities.

[0068] According to some embodiments of the present invention, the time dispersion characteristics of the multipath effect are cleverly utilized, and the type of communication environment is determined by an algorithm model constructed based on prior knowledge of channel time dispersion parameters (for example, the average excess delay and mean square delay spread of non-line-of-sight propagation are greater than those of line-of-sight propagation, the average excess delay and mean square delay spread of outdoor environments are greater than those of indoor environments, the number of multipaths in outdoor environments is less than that in indoor environments, etc.), thereby effectively improving the efficiency and accuracy of environmental determination.

[0069] It should be understood that some of the block diagrams shown in the accompanying drawings of the present invention are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0070] It should also be understood that in some alternative embodiments, the functions / steps included in the foregoing method may not occur in the order shown in the flow chart. For example, two functions / steps shown in sequence may be performed substantially simultaneously or even in reverse order. This specifically depends on the functions / steps involved.

[0071] In addition, it is easy for those skilled in the art to understand that the methods provided by one or more embodiments of the present invention can be implemented by computer programs. For example, when a computer storage medium (such as a USB flash drive) storing the computer program is connected to a computer, the methods of one or more embodiments of the present invention can be executed by running the computer program.

[0072] Although only some of the embodiments of the present invention are described above, it should be understood by those skilled in the art that the present invention can be implemented in many other forms without departing from its subject matter and scope. Therefore, the examples and embodiments shown are considered to be illustrative rather than restrictive, and the present invention may include various modifications and substitutions without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A method for determining vehicle communication environment based on ultra-wideband, characterized in that: The following steps are involved: The vehicle-side ultra-wideband receiver detects the ultra-wideband signal sent by the vehicle-side ultra-wideband transmitter; Determine a channel impulse response in a current ultra-wideband communication process based on the detected ultra-wideband signal; Based on the channel impulse response, calculating a channel time dispersion parameter; Inputting the channel time dispersion parameter into an algorithm model, and generating first judgment information indicating a current communication environment type based on the algorithm model, wherein the current communication environment type includes whether the vehicle is indoors or outdoors; as well as Based on the first judgment information, positioning model parameters for the current communication environment type are determined.

2. The method according to claim 1, wherein: The channel time dispersion parameters include one or more of the following: the number of multipaths, the amplitude and delay of each multipath component, the average excess delay, the mean square delay spread, and the maximum multipath delay.

3. The method according to claim 1, wherein: The algorithm model includes a machine learning model, which is constructed based on a training data set containing channel time dispersion parameter samples and annotation information characterizing the communication environment type corresponding to the samples.

4. The method according to claim 1, wherein: The algorithm model includes a threshold classification model, and the channel time dispersion parameter is input into the algorithm model, and generating first judgment information indicating the type of the current communication environment based on the algorithm model includes: Acquire the line-of-sight type of current ultra-wideband communication, wherein the line-of-sight type includes line-of-sight propagation and non-line-of-sight propagation; determining a dispersion parameter threshold corresponding to the line-of-sight type; comparing the channel time dispersion parameter with the dispersion parameter threshold; and The current communication environment type is determined based on the comparison result.

5. The method according to claim 4, wherein: The thresholds of average excess delay and mean square delay spread for non-line-of-sight propagation are respectively greater than the thresholds of average excess delay and mean square delay spread for line-of-sight propagation.

6. A data processing device for determining the type of vehicle communication environment, comprising: Memory; processor; as well as A computer program stored on the memory and executable on the processor, the execution of the computer program causing the following steps to be performed: A. determining a channel impulse response in a current ultra-wideband communication process based on an ultra-wideband signal sent by a vehicle-side ultra-wideband transmitter and detected by a vehicle-side ultra-wideband receiver; B. calculating a channel time dispersion parameter based on the channel impulse response; C. inputting the channel time dispersion parameter into an algorithm model, and generating first judgment information indicating a current communication environment type based on the algorithm model, wherein the current communication environment type includes whether the vehicle is indoors or outdoors; as well as D. Based on the first judgment information, determine positioning model parameters for the current communication environment type.

7. The device according to claim 6, wherein: The algorithm model includes a threshold classification model, and the operation of the computer program causes step C to be performed in the following manner: C1. Obtaining the line-of-sight type of the current ultra-wideband communication, wherein the line-of-sight type includes line-of-sight propagation and non-line-of-sight propagation; C2. determining a dispersion parameter threshold corresponding to the line-of-sight type; C3. Compare the channel time dispersion parameter with the dispersion parameter threshold; and C4. Determine the current communication environment type based on the comparison result.

8. The device according to claim 7, wherein: The thresholds of average excess delay and mean square delay spread for non-line-of-sight propagation are respectively greater than the thresholds of average excess delay and mean square delay spread for line-of-sight propagation.

9. A vehicle, characterized in that: include: Ultra-wideband transmitter; An ultra-wideband receiver for detecting an ultra-wideband signal sent by an ultra-wideband transmitter; as well as A data processing device as claimed in any one of claims 6 to 8.

10. A computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, characterized in that: When the instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 5.

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