Indoor target vehicle positioning method, device, equipment and product

Abstract

The invention discloses an indoor target vehicle positioning method, device, equipment and product, and the method comprises the steps: obtaining local estimation value models of two sensors through building a measurement model and a leak detection model, and further carrying out the positioning of an indoor target vehicle according to the local estimation value models of the two sensors and a set preset constraint condition; and obtaining an estimated value model of the positioning information of the indoor target vehicle, and positioning the indoor target vehicle by using the estimated value model. The invention discloses a method, a device, equipment and a product for positioning an indoor target vehicle. The method, the device, the equipment and the product have the characteristics of high positioning precision of the indoor target vehicle, high reliability and small calculated amount.

Description

Technical Field

[0001] The present invention belongs to the field of target positioning, and in particular relates to a method, device, equipment and product for positioning an indoor target vehicle. Background Art

[0002] The positioning of indoor unmanned ground vehicles is widely used in environmental monitoring, environmental search, intelligent logistics and other fields. Reliable and accurate positioning information ensures the safety and intelligence of the target vehicle. Due to different positioning principles, the positioning effects of different types of sensors are also different. For example, under harsh lighting conditions, the low-quality visual information obtained reduces the positioning performance of the camera sensor; due to the influence of measurement noise, ultra-wideband UWB sensor positioning is prone to produce non-smooth positioning trajectories; inertial measurement units (IMUs) can obtain acceleration and angular velocity, but there are problems of accumulation and offset errors in target positioning. Therefore, a single sensor for indoor target vehicle positioning has problems of poor positioning accuracy and weak environmental adaptability. Summary of the invention

[0003] In view of this, the present invention aims to overcome the defects in the prior art and proposes a method, device, equipment and product for positioning a target vehicle indoors.

[0004] To achieve the above object, the technical solution of the present invention is achieved as follows: In a first aspect, the present invention discloses a method for positioning an indoor target vehicle, comprising: According to the two-dimensional motion models corresponding to the first sensor and the second sensor, the measurement models of the first sensor and the second sensor are respectively established, the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; Establishing missed detection models of the first sensor and the second sensor respectively, wherein the missed detection models are used to characterize whether the corresponding sensors output measurement information; According to the two-dimensional motion model, measurement model and missed detection model corresponding to the first sensor and the second sensor, local estimator models of the first sensor and the second sensor are respectively established, and the local estimator models are used to characterize the estimation value of the corresponding sensor for the indoor target vehicle positioning; According to preset constraints and two local estimator models, an estimation value model capable of obtaining indoor target vehicle positioning information according to measurement information of the first sensor and the second sensor is obtained, and the indoor target vehicle is positioned using the estimation value model.

[0005] In one embodiment of the present invention, local estimator models of the first sensor and the second sensor are respectively established according to the two-dimensional motion model, measurement model and missed detection model corresponding to the first sensor and the second sensor, including: aligning the estimated values ​​output by the two local estimator models in sampling time.

[0006] In one embodiment of the present invention, the preset constraint conditions include: the distance between the coordinate origin of the first sensor and the coordinate origin of the second sensor is fixed, and the speeds of the target vehicle measured by the first sensor and the second sensor are the same.

[0007] In one embodiment of the present invention, the missed detection model is a binary function.

[0008] In one embodiment of the present invention, when the value of the binary function is 1, it indicates that the corresponding sensor has output measurement information; and when the value of the binary function is 0, it indicates that the corresponding sensor has no output measurement information.

[0009] In one embodiment of the present invention, obtaining an estimated value model of indoor target vehicle positioning information and using the estimated value model to locate the indoor target vehicle includes: using the estimated value model to obtain an estimated value and covariance of the indoor target vehicle positioning.

[0010] In a second aspect, the present invention discloses a positioning device for an indoor target vehicle, the device comprising: A measurement model generation module is used to establish measurement models of the first sensor and the second sensor respectively according to the two-dimensional motion models corresponding to the first sensor and the second sensor, wherein the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; and the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; A missed detection model generation module, used to establish missed detection models of the first sensor and the second sensor respectively, the missed detection models are used to characterize whether the corresponding sensors output measurement information; A local estimator model generation module is used to establish local estimator models of the first sensor and the second sensor respectively according to the two-dimensional motion model, the measurement model and the missed detection model corresponding to the first sensor and the second sensor, and the local estimator model is used to characterize the estimation value of the corresponding sensor for the indoor target vehicle positioning; The positioning module is used to obtain an estimation value model that can obtain indoor target vehicle positioning information based on the measurement information of the first sensor and the second sensor according to preset constraints and two local estimator models, and use the estimation value model to locate the indoor target vehicle.

[0011] In a third aspect, the present invention discloses an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above method.

[0012] In a fourth aspect, the present invention discloses a computer-readable storage medium having a computer program stored thereon, which implements the above method when executed by a processor.

[0013] In a fifth aspect, a computer program product comprises a computer program, and the computer program implements the above method when executed by a processor.

[0014] Compared with the prior art, the present invention has the following advantages: The present invention discloses a method, device, equipment and product for positioning a target vehicle indoors. By establishing a measurement model and a missed detection model, local estimator models of two sensors are obtained. Further, according to the local estimator models of the two sensors and preset constraints, an estimated value model of the positioning information of the target vehicle indoors is obtained and the target vehicle indoors is positioned using the estimated value model. The present invention discloses a method, device, equipment and product for positioning a target vehicle indoors, which has the characteristics of high positioning accuracy, high reliability and small calculation amount for the target vehicle indoors. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0016] In the attached picture: Figure 1 A schematic diagram of an application scenario of a method for positioning an indoor target vehicle according to an embodiment of the present invention; Figure 2 A schematic diagram of a method for positioning an indoor target vehicle according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the principle of a method for positioning an indoor target vehicle according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a positioning device for an indoor target vehicle according to an embodiment of the present invention; Figure 5 This is a schematic diagram of an electronic device for positioning a target vehicle indoors according to an embodiment of the present invention; Figure 6 A schematic diagram of a location trajectory of an indoor target vehicle positioning method according to an embodiment of the present invention; Figure 7 A schematic diagram of position error covariance of a method for positioning an indoor target vehicle according to an embodiment of the present invention; Figure 8 A schematic diagram of velocity error covariance of a method for positioning an indoor target vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0018] In the description of the present invention, it should be further explained that the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0019] The present invention discloses an indoor target vehicle positioning method, device, equipment and product application scenarios such as Figure 1 As shown, under the existing technical conditions, due to the different positioning principles, the positioning effects of different types of sensors are also different. For example, under harsh lighting conditions, the low-quality visual information obtained reduces the positioning performance of the camera sensor; due to the influence of measurement noise, ultra-wideband UWB sensor positioning is prone to produce non-smooth positioning trajectories; inertial measurement unit IMU can obtain acceleration and angular velocity, but there are problems of accumulation and offset errors in target positioning, so a single sensor performs indoor target vehicle positioning, which has the problems of poor positioning accuracy and weak environmental adaptability. The present invention discloses a method, device, equipment and product for positioning indoor target vehicles, which obtains local estimator models of two sensors by establishing a measurement model and a missed detection model, and further obtains an estimated value model of indoor target vehicle positioning information according to the local estimator models of the two sensors and the preset constraints set, and uses the estimated value model to locate the indoor target vehicle, which has the characteristics of high positioning accuracy, high reliability and small calculation amount for indoor target vehicles.

[0020] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0021] In one embodiment of the present invention, Figure 2 As shown, a method for positioning an indoor target vehicle includes: Step S201, according to the two-dimensional motion models corresponding to the first sensor and the second sensor, respectively establish measurement models of the first sensor and the second sensor, the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; Exemplarily, the first sensor is a camera sensor, the second sensor is an ultra-wideband UWB sensor, and the two-dimensional motion model is expressed as follows:

[0022] in, represents the camera sensor, represents ultra-wideband UWB sensor, is the target state, and are the longitudinal position and velocity, and are the horizontal position and velocity, and are the status update moments of the camera sensor and the ultra-wideband UWB sensor, respectively. In this embodiment, represents the sampling period of the camera sensor, Represents the sampling period of the ultra-wideband UWB sensor; represents process noise, which is zero-mean Gaussian white noise; the covariance is known to be expressed as ,in, , It is a 4*4 dimensional identity matrix; For example, in this embodiment, s and s; The measurement model is expressed as :

[0023] represents the camera sensor, represents ultra-wideband UWB sensor; and The covariances are and Zero-mean white noise; , ; I 2 is the 2*2 dimensional identity matrix.

[0024] Step S202, respectively establishing missed detection models of the first sensor and the second sensor, the missed detection models being used to characterize whether the corresponding sensors output measurement information; In this embodiment, the missed detection model is a binary function.

[0025] In this embodiment, when the value of the binary function is 1, it indicates that the corresponding sensor has output measurement information; when the value of the binary function is 0, it indicates that the corresponding sensor does not have output measurement information, that is, missed detection.

[0026] For example, the binary function is expressed as ;

[0027] Step S203: Figure 2 and Figure 3 As shown, according to the two-dimensional motion model, measurement model and missed detection model corresponding to the first sensor and the second sensor, local estimator models of the first sensor and the second sensor are respectively established, and the local estimator model is used to characterize the estimation value of the corresponding sensor for the indoor target vehicle positioning; Exemplarily, the estimated value of the local estimator model is expressed as , the covariance is expressed as , the local estimator model is expressed as follows:

[0028] in, and are the forecast estimates and their covariances, and are the new information and the covariance of the new information, respectively. is the estimator gain, is the identity matrix.

[0029] Step S204, as Figure 2 and Figure 3 As shown, according to preset constraints, two local estimator models are used to obtain an estimation model that can obtain indoor target vehicle positioning information based on the measurement information of the first sensor and the second sensor, and the indoor target vehicle is positioned using the estimation model.

[0030] In this embodiment, obtaining an estimated value model of indoor target vehicle positioning information and using the estimated value model to locate the indoor target vehicle includes: using the estimated value model to obtain an estimated value and covariance of the indoor target vehicle positioning.

[0031] In this embodiment, the estimated value of the estimated value model is expressed as , the covariance is expressed as :

[0032]

[0033]

[0034]

[0035] in, is the estimated value covariance of the local estimator model of the ultra-wideband UWB sensor, is the estimated covariance of the local estimator model of the camera sensor, is the cross covariance between the two; and are the longitudinal distance and lateral distance from the origin of the coordinate system in the camera sensor to the origin of the coordinate system in the ultra-wideband UWB sensor, respectively; I 4 is the 4*4 dimensional identity matrix.

[0036] Based on the previous embodiment, in another embodiment of the present invention, local estimator models of the first sensor and the second sensor are respectively established according to the two-dimensional motion model, measurement model and missed detection model corresponding to the first sensor and the second sensor, including: aligning the estimated values ​​output by the two local estimator models in sampling time.

[0037] For example, since the sampling periods of the camera sensor and the ultra-wideband UWB sensor are inconsistent and the sampling frequency of the camera sensor is high, the estimated value of the ultra-wideband UWB sensor is predicted according to the motion model. time period, and the estimated value results of the local estimator model of the camera sensor are aligned in time, then The estimated value of the ultra-wideband UWB sensor at time is:

[0038]

[0039] In this embodiment, the alignment of sampling time can effectively improve the fusion effect of the first sensor and the second sensor, and enhance the final positioning accuracy of the target vehicle.

[0040] Based on the previous embodiment, in another embodiment of the present invention, the preset constraint conditions include: the distance between the coordinate origin of the first sensor and the coordinate origin of the second sensor is fixed, and the speeds of the target vehicle measured by the first sensor and the second sensor are the same.

[0041] For example, and They are the longitudinal distance and lateral distance from the origin of the coordinate system in the camera sensor to the origin of the coordinate system in the ultra-wideband UWB sensor. Since the image label to be recognized by the camera and the position of the ultra-wideband UWB sensor are both known and fixed a priori, the distance constraints are as follows: Among them, the position coordinates It is the position with the camera sensor as the coordinate origin, the position coordinate It is the position with the ultra-wideband UWB sensor as the coordinate origin.

[0042] For example, the speed of the same indoor target vehicle measured by the camera sensor and the ultra-wideband UWB sensor should be consistent, so the speed constraint is as follows: is the longitudinal speed of the target vehicle measured by the ultra-wideband UWB sensor, is the longitudinal velocity of the target vehicle measured by the camera sensor, It is the lateral speed of the target vehicle measured by the ultra-wideband UWB sensor. It is the longitudinal velocity of the target vehicle measured by the camera sensor.

[0043] In this embodiment, the setting of constraint conditions can improve the accuracy of the estimation model and enhance the final positioning accuracy of the target vehicle.

[0044] like Figure 6 As shown, the proposed method is smoother and has less noise than the camera sensor data alone and the ultra-wideband UWB sensor data alone.

[0045] like Figure 7 As shown in Figure 3, the estimated value error covariance of this method decreases in position, reflecting that the positioning accuracy of the fused target is higher than that of a single sensor.

[0046] like Figure 8 As shown in Figure 2, the estimated value error covariance of this method decreases in speed, reflecting that the positioning accuracy of the fused target is higher than that of a single sensor.

[0047] like Figure 4 As shown, the present invention also discloses a positioning device for an indoor target vehicle, comprising: The measurement model generation module 401 is used to establish the measurement models of the first sensor and the second sensor respectively according to the two-dimensional motion models corresponding to the first sensor and the second sensor, wherein the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; and the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; A missed detection model generating module 402, used to respectively establish missed detection models of the first sensor and the second sensor, wherein the missed detection models are used to characterize whether the corresponding sensors output measurement information; A local estimator model generation module 403 is used to establish local estimator models of the first sensor and the second sensor respectively according to the two-dimensional motion model, measurement model and missed detection model corresponding to the first sensor and the second sensor, and the local estimator model is used to characterize the estimation value of the corresponding sensor for the indoor target vehicle positioning; The positioning module 404 is used to obtain an estimation model that can obtain the indoor target vehicle positioning information based on the measurement information of the first sensor and the second sensor according to the preset constraints and two local estimator models, and use the estimation model to locate the indoor target vehicle.

[0048] The present invention also discloses an electronic device, such as Figure 5 As shown, an embodiment is disclosed, which is a block diagram of an electronic device suitable for positioning the above-mentioned indoor target vehicle.

[0049] The electronic device 50 of this embodiment includes a processor 501, which can perform various appropriate actions and processes according to the program stored in the ROM 502 or the program loaded from the storage part 508 to the RAM 503. The processor 501 may include, for example, a general-purpose microprocessor, an instruction set processor and / or a related chipset and / or a dedicated microprocessor, etc. The processor 501 may also include an onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present invention.

[0050] In RAM503, various programs and data required for the operation of electronic device 50 are stored. Processor 501, ROM502 and RAM503 are connected to each other via bus 504, and processor 501 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM502 and / or RAM503. It should be noted that the program can also be stored in one or more memories other than ROM502 and RAM503, and processor 501 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in one or more memories.

[0051] According to an embodiment of the present invention, the electronic device 50 may further include an I / O interface 505, which is also connected to the bus 504. The electronic device 50 may further include one or more of the following components connected to the I / O interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube, a liquid crystal display, and a speaker; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 5010 is also connected to the I / O interface 505 as needed. A removable medium 5011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 5010 as needed, so that a computer program read therefrom is installed into the storage portion 508 as needed.

[0052] The present invention also provides a computer-readable storage medium.

[0053] The computer-readable storage medium may be included in the electronic device / device system described in the above embodiment; or it may exist independently without being assembled into the electronic device / device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0054] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory RAM, a read-only memory ROM, an erasable programmable read-only memory EPROM or a flash memory, a portable compact disk read-only memory CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus, or device.

[0055] Embodiments of the present invention also include a computer program product.

[0056] The computer program product includes a computer program, which contains program codes for executing the method provided by the embodiment of the present invention. When the computer program product runs on an electronic device, the program codes are used to enable the electronic device to implement the method provided by the embodiment of the present invention.

[0057] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium. The program code included in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0058] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written by any combination of one or more programming languages, and specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages. Programming languages ​​include but are not limited to programming languages ​​such as Java, C++, python, C language or similar. The program code can be executed completely on the user computing device, partially on the user device, partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network or a wide area network, or can be connected to an external computing device.

[0059] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present invention can be combined and / or combined in various ways, even if such a combination or combination is not explicitly recorded in the present invention. In particular, without departing from the spirit and teaching of the present invention, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0060] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination. The scope of the present invention is limited by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for positioning a target vehicle indoors, characterized in that: include: According to the two-dimensional motion models corresponding to the first sensor and the second sensor, respectively establish the measurement models of the first sensor and the second sensor, wherein the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; and the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; Establishing missed detection models of the first sensor and the second sensor respectively, wherein the missed detection models are used to characterize whether the corresponding sensors output measurement information; According to the two-dimensional motion model, the measurement model and the missed detection model corresponding to the first sensor and the second sensor, respectively establish a local estimator model of the first sensor and the second sensor, wherein the local estimator model is used to characterize an estimation value of the corresponding sensor for positioning the indoor target vehicle; According to preset constraints, the two local estimator models obtain an estimation value model that can obtain indoor target vehicle positioning information based on the measurement information of the first sensor and the second sensor, and use the estimation value model to locate the indoor target vehicle.

2. A method for positioning an indoor target vehicle according to claim 1, characterized in that: The local estimator models of the first sensor and the second sensor are respectively established according to the two-dimensional motion model, the measurement model and the missed detection model corresponding to the first sensor and the second sensor, including: aligning the estimated values ​​output by the two local estimator models in sampling time.

3. A method for positioning an indoor target vehicle according to claim 1, characterized in that: The preset constraint conditions include: a distance between a coordinate origin of the first sensor and a coordinate origin of the second sensor is fixed, and the speeds of the target vehicle measured by the first sensor and the second sensor are the same.

4. A method for positioning an indoor target vehicle according to claim 1, characterized in that: The missed detection model is a binary function.

5. A method for positioning an indoor target vehicle according to claim 4, characterized in that: When the value of the binary function is 1, it indicates that the corresponding sensor has output measurement information; when the value of the binary function is 0, it indicates that the corresponding sensor does not have output measurement information.

6. A method for positioning an indoor target vehicle according to claim 1, characterized in that: The method of obtaining an estimated value model for indoor target vehicle positioning information and using the estimated value model to locate the indoor target vehicle includes: using the estimated value model to obtain an estimated value and covariance for indoor target vehicle positioning.

7. A positioning device for an indoor target vehicle, characterized in that: The device comprises: A measurement model generation module, used to establish measurement models of the first sensor and the second sensor respectively according to the two-dimensional motion models corresponding to the first sensor and the second sensor, wherein the two-dimensional motion model is used to characterize the changing relationship between the position and speed of the target vehicle; and the measurement model is used to characterize the measurement value of the corresponding sensor for positioning the indoor target vehicle; A missed detection model generation module, used to respectively establish missed detection models of the first sensor and the second sensor, wherein the missed detection models are used to characterize whether the corresponding sensors output measurement information; A local estimator model generation module, used to establish local estimator models of the first sensor and the second sensor respectively according to the two-dimensional motion model, the measurement model and the missed detection model corresponding to the first sensor and the second sensor, wherein the local estimator model is used to characterize the estimation value of the corresponding sensor for the indoor target vehicle positioning; A positioning module is used to obtain an estimation value model that can obtain the indoor target vehicle positioning information based on the measurement information of the first sensor and the second sensor according to preset constraints and the two local estimator models, and use the estimation value model to locate the indoor target vehicle.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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