WO2023098005A1 - 用于超高速移动物体的基站通信覆盖方法及相关设备 - Google Patents

用于超高速移动物体的基站通信覆盖方法及相关设备 Download PDF

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Publication number
WO2023098005A1
WO2023098005A1 PCT/CN2022/096979 CN2022096979W WO2023098005A1 WO 2023098005 A1 WO2023098005 A1 WO 2023098005A1 CN 2022096979 W CN2022096979 W CN 2022096979W WO 2023098005 A1 WO2023098005 A1 WO 2023098005A1
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Prior art keywords
base station
target object
information
position information
communication coverage
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PCT/CN2022/096979
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English (en)
French (fr)
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韩书君
严凯文
董辰
许晓东
王碧舳
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北京邮电大学
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Publication of WO2023098005A1 publication Critical patent/WO2023098005A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0408—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas using two or more beams, i.e. beam diversity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present disclosure relates to the technical field of wireless communication, and in particular to a base station communication coverage method and related equipment for ultra-high-speed moving objects.
  • Beamforming is a signal preprocessing technology based on antenna arrays. Beamforming generates directional beams by adjusting the weighting coefficients of each array element in the antenna array, so that significant array gain can be obtained.
  • the performance gain of beamforming mainly comes from directional communication.
  • the transmitter and receiver need to work together to ensure that the directions of the transmit and receive beams are properly aligned, a process commonly referred to as beamfinding.
  • the most commonly used beam finding method based on feedback mechanism includes multiple processes such as beam scanning, beam measurement, beam determination and beam reporting.
  • the efficient communication of base station beamforming technology relies on the beam alignment of the transmitting and receiving nodes, that is, the beam selection process, which will increase resource overhead and cause delays in the establishment of communication connections in the context of objects moving at ultra-high speeds.
  • the purpose of the present disclosure is to propose a base station communication coverage method and related equipment for ultra-high-speed moving objects.
  • the present disclosure provides a base station communication coverage method for ultra-high-speed moving objects, including:
  • the base station communication coverage method further includes:
  • the obtaining the current position information, motion information and position information of the base station of the target object through the computer vision CV algorithm based on the moving image includes:
  • ⁇ a (x a , y a , z a )
  • ⁇ ab represents the angle of arrival
  • x a , y a , z a represent the three-dimensional coordinate values of the current location information respectively
  • x b , y b , z b represent the three-dimensional coordinate values of the base station respectively.
  • phase information corresponding to each antenna in the base station is obtained through calculation based on the angle of arrival, including: the phase information is specifically:
  • t1 represents the phase corresponding to each antenna
  • l a, 2, ..., L
  • L represents the number of antennas that the base station performs communication coverage on the target object
  • ⁇ represents the wavelength of the base station sending information
  • performing beamforming on the target object based on the phase information includes:
  • a beamforming vector is determined based on the phase information, and beamforming is performed on the target object based on the beamforming vector.
  • predicted position is specifically expressed as:
  • x a , y a , z a respectively represent the three-dimensional coordinate values of the current position information
  • v represents the moving speed of the target object
  • ⁇ represents the speed direction of the target object
  • t represents the frame rate of the moving image
  • the present disclosure also provides a base station communication coverage device for ultra-high-speed moving objects, including:
  • An image acquisition module configured to acquire a moving image of a target object
  • a calculation module configured to obtain the current position information and motion information of the target object and the position information of the base station through a computer vision CV algorithm based on the moving image;
  • an angle of arrival determination module configured to determine an angle of arrival between the target object and a base station antenna based on the current position information, the motion information, and the position information of the base station;
  • a phase information determination module configured to obtain phase information corresponding to each antenna in the base station through calculation based on the angle of arrival
  • a beamforming module configured to perform beamforming on the target object based on the phase information
  • a position prediction module configured to determine a predicted position of the target object based on the current position information and the motion information
  • a determination module configured to return to the image acquisition module in response to determining that the predicted location is within the communication coverage of the base station, and complete the image acquisition module in response to determining that the predicted location is not within the communication coverage of the base station. The communication coverage of the target object.
  • the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable by the processor.
  • the processor executes the computer program, it realizes The base station communication coverage method as described above.
  • the present disclosure also provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to perform the above-mentioned base station communication override method.
  • the base station communication coverage method and related equipment for ultra-high-speed moving objects determine the current position information of the target object through the CV algorithm, and determine the angle of arrival based on the current position information and the position information of the base station , to determine the phase information of each antenna in the base station based on the angle of arrival. Based on the phase information, the communication link between the base station and the target object is established, so as to determine the beam and complete the beamforming and communication coverage.
  • the disclosed base station communication coverage method for ultra-high-speed moving objects performs beam selection based on location information, effectively narrows the beam scanning range, and further improves the efficiency and accuracy of beam selection.
  • FIG. 1 is a schematic flowchart of a base station communication coverage method for an ultra-high-speed moving object according to an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a communication scene between a base station and a target object according to an embodiment of the present disclosure
  • FIG. 3 is a schematic structural diagram of a base station communication coverage device for an ultra-high-speed moving object according to an embodiment of the present disclosure
  • FIG. 4 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present disclosure.
  • the efficient communication of base station beamforming technology depends on the beam alignment of the transmitting and receiving nodes, that is, the beam selection process.
  • the beam selection process In the context of ultra-high-speed mobility, resource overhead and communication connection establishment delays will be increased.
  • Feedback-based beamforming The selection is not suitable for communication coverage of ultra-high-speed moving objects. Therefore, position-aware beam selection becomes a viable alternative to feedback-based beam selection.
  • the basic idea of this method is to use the location of the receiver to determine the downlink beam from the transmitter to the receiver.
  • the disclosure discloses a base station communication coverage method for an ultra-high-speed moving object, which performs beam selection based on position information, narrows the beam scanning range, and further improves the efficiency and accuracy of beam selection.
  • the present disclosure provides a base station communication coverage method for ultra-high-speed moving objects. Referring to FIG. 1, the method includes the following steps:
  • Step S1 acquiring a moving image of a target object.
  • the base station in this embodiment is a 5G base station, and the communication device includes a camera, CV (Computer Vision, computer vision) equipment, antenna, positioning equipment, and a phase controller.
  • the moving image of the target object is obtained through the camera, and the communication coverage of the target object is carried out through the antenna, positioning equipment and phase controller.
  • Step S2. Obtain the current position information and motion information of the target object and the position information of the base station through computer vision CV algorithm based on the moving image.
  • the moving image is calculated by the CV equipment set on the base station to obtain the position information and motion information of the target object.
  • the position information of the base station is determined at the same time, that is, the relative position of the target object and the base station is obtained. relation.
  • Step S3 determining the angle of arrival between the target object and the base station antenna based on the current position information, motion information and base station position information.
  • ⁇ a (x a , y a , z a )
  • ⁇ ab represents the angle of arrival
  • x a , y a , and z a represent the three-dimensional coordinate values of the current location information respectively
  • x b , y b , z b represent the three-dimensional coordinate values of the base station respectively.
  • Step S4 obtaining phase information corresponding to each antenna in the base station through calculation based on the angle of arrival.
  • phase expression is specifically:
  • t l represents the phase corresponding to each antenna
  • l 1, 2, ..., L
  • L represents the number of antennas that the base station performs communication coverage on the target object
  • ⁇ represents the wavelength of the base station sending information
  • the antenna array in the base station is Evenly distributed, the distance interval between adjacent antennas is l/2.
  • Step S5 performing beamforming on the target object based on the phase information.
  • the base station After the phase information is obtained through calculation, the base station establishes a directional communication link with the target object according to the phase information, thereby completing the beamforming of the target object.
  • Step S6 Determine the predicted position of the target object based on the current position information and motion information.
  • the target object in this embodiment is a high-speed moving object, such as a running high-speed rail, because the trajectory of the high-speed rail is determined, so the position of the high-speed rail at the next moment can be predicted more accurately based on the current position information and motion information .
  • Step S7 In response to determining that the predicted position is within the communication coverage of the base station, return to S1. In response to determining that the predicted position is not within the communication coverage of the base station, complete the communication coverage of the target object.
  • the predicted position it is judged whether to continue to carry out communication coverage on the target object. If the predicted position is included in the communication coverage area, continue to carry out communication coverage on the target object. If the predicted position is not included in the communication coverage area, it means that the target object Once you have left the communication coverage area, you can stop the communication coverage of the target object.
  • the camera when the high-speed rail moves near the base station at high speed, the camera will detect the high-speed rail in advance and determine the position of the high-speed rail through the CV algorithm because the camera's line-of-sight distance is higher than the communication distance of the base station At the same time, the driving direction and trajectory of the high-speed rail are determined, and the position of the high-speed rail at the next moment can be estimated according to the current position information and motion information of the high-speed rail. If the position at the next moment is within the communication range of the base station, the communication coverage for the high-speed rail will continue, and if the position at the next moment is not within the communication range of the base station, the communication coverage for the high-speed rail will be completed.
  • the communication coverage method of this embodiment can narrow the search range of the predetermined beam scanning direction, and improve the communication efficiency of the beamforming.
  • step S2 before step S2, it also includes: detecting the category of the target object based on the computer vision CV algorithm, in response to determining that the target object belongs to the preset object category, performing step S2, in response to determining that the target object does not belong to the preset category When the object category is set, return to step S1.
  • the preset object category is high-speed rail.
  • the CV device detects that the target object is high-speed rail, it calculates the moving image of the high-speed rail to further determine the current location information, motion information and location information of the high-speed rail.
  • obtaining the current position information, motion information and position information of the base station of the target object through the computer vision CV algorithm based on the moving image includes:
  • the moving image is calculated by a second target detection algorithm to obtain current position information, motion information and position information of the base station of the target object.
  • the first target detection algorithm in this embodiment refers to the target detection and distance estimation method of the patent application publication number CN111460919A.
  • the second target detection algorithm in this embodiment refers to the night target detection and tracking method of patent application publication number CN100546380C.
  • the base station needs to use the existing beamforming method to cover the target object through communication, that is, through feedback-based
  • the beam selection method performs beamforming on the target object.
  • the specific method of this beamforming belongs to the prior art, and will not be repeated here.
  • performing beamforming on the target object based on the phase information includes: determining a beamforming vector based on the phase information, and performing beamforming on the target object based on the beamforming vector.
  • the beamforming vector is specifically:
  • W [w 1 , w 2 , ..., w l , ... w L ]
  • the base station performs beamforming on the target object.
  • the predicted position is specifically expressed as:
  • ⁇ at (x a + v t sin ⁇ , y a + v cos ⁇ , z a )
  • x a , y a , z a respectively represent the three-dimensional coordinate value of the current position information
  • v represents the moving speed of the target object
  • ⁇ represents the speed direction of the target object
  • t represents the frame rate of the moving image
  • the methods in the embodiments of the present disclosure may be executed by a single device, such as a computer or a server.
  • the method of this embodiment can also be applied in a distributed scenario, and is completed by cooperation of multiple devices.
  • one of the multiple devices may only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete all The base station communication coverage method described above.
  • the present disclosure also provides a base station communication coverage device for an ultra-high-speed moving object.
  • the base station communication coverage device for ultra-high-speed moving objects includes:
  • An image acquisition module 301 configured to acquire a moving image of a target object
  • Calculation module 302 is configured to obtain the current position information and motion information of the target object and the position information of the base station through the computer vision CV algorithm based on the moving image;
  • the angle of arrival determination module 303 is configured to determine the angle of arrival between the target object and the base station antenna based on the current position information, motion information and position information of the base station;
  • the phase information determination module 304 is configured to obtain the phase information corresponding to each antenna in the base station through calculation based on the angle of arrival;
  • the beamforming module 305 is configured to perform beamforming on the target object based on the phase information
  • the position prediction module 306 is configured to determine the predicted position of the target object based on the current position information and motion information;
  • the determination module 307 is configured to return to the image acquisition module 301 in response to determining that the predicted position is within the communication coverage range of the base station and the target object, and complete the detection of the target object in response to determining that the predicted position is not within the communication coverage range of the base station and the target object. communication coverage.
  • a category determination module 308 is also included, configured to detect the category of the target object based on a computer vision CV algorithm,
  • the calculation module 302 is specifically configured to obtain the current position information, motion information and base station position information of the target object through the computer vision CV algorithm based on the moving image, including:
  • the moving image is calculated by a second target detection algorithm to obtain current position information, motion information and position information of the base station of the target object.
  • the angle-of-arrival determination module 303 is specifically configured such that the calculation expression for the angle-of-arrival is:
  • ⁇ a (x a , y a , z a )
  • ⁇ ab represents the angle of arrival
  • x a , y a , and z a represent the three-dimensional coordinate values of the current location information respectively
  • x b , y b , z b represent the three-dimensional coordinate values of the base station respectively.
  • the phase information determination module 304 is specifically configured to obtain the phase information corresponding to each antenna in the base station through calculation based on the angle of arrival, including: the phase information is specifically:
  • t l represents the phase corresponding to each antenna
  • l 1, 2, ..., L
  • L represents the number of antennas for the base station to communicate with the target object
  • ⁇ represents the wavelength of the base station sending information
  • the distance between adjacent antennas The distance interval is l/2.
  • the beamforming module 305 is specifically configured to perform beamforming on the target object based on phase information, including:
  • a beamforming vector is determined based on the phase information, and beamforming is performed on the target object based on the beamforming vector.
  • the position prediction module 306 is specifically configured to predict a position as follows:
  • ⁇ at (x a + v t sin ⁇ , y a + v cos ⁇ , z a )
  • x a , y a , z a respectively represent the three-dimensional coordinate value of the current position information
  • v represents the moving speed of the target object
  • ⁇ represents the speed direction of the target object
  • t represents the frame rate of the moving image
  • the device in the above embodiments is used to implement the corresponding base station communication coverage method for ultra-high-speed moving objects in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
  • the present disclosure also provides an electronic device corresponding to the method in any of the above embodiments, including a memory, a processor, and a computer program stored in the memory and operable on the processor, and the processor executes the program When implementing the base station communication coverage method for ultra-high-speed moving objects in any one of the above embodiments.
  • FIG. 4 shows a schematic diagram of a more specific hardware structure of an electronic device provided by this embodiment.
  • the device may include: a processor 1010 , a memory 1020 , an input/output interface 1030 , a communication interface 1040 and a bus 1050 .
  • the processor 1010 , the memory 1020 , the input/output interface 1030 and the communication interface 1040 are connected to each other within the device through the bus 1050 .
  • the processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit, central processing unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute related programs to realize the technical solutions provided by the embodiments of this specification.
  • a general-purpose CPU Central Processing Unit, central processing unit
  • a microprocessor an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits
  • ASIC Application Specific Integrated Circuit
  • the memory 1020 can be implemented in the form of ROM (Read Only Memory, read-only memory), RAM (Random Access Memory, random access memory), static storage device, dynamic storage device, and the like.
  • the memory 1020 can store operating systems and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1020 and invoked by the processor 1010 for execution.
  • the input/output interface 1030 is used to connect the input/output module to realize information input and output.
  • the input/output/module can be configured in the device as a component (not shown in the figure), or can be externally connected to the device to provide corresponding functions.
  • the input device may include a keyboard, mouse, touch screen, microphone, various sensors, etc.
  • the output device may include a display, a speaker, a vibrator, an indicator light, and the like.
  • the communication interface 1040 is used to connect a communication module (not shown in the figure), so as to realize the communication interaction between the device and other devices.
  • the communication module can realize communication through wired means (such as USB, network cable, etc.), and can also realize communication through wireless means (such as mobile network, WIFI, Bluetooth, etc.).
  • Bus 1050 includes a path that carries information between the various components of the device (eg, processor 1010, memory 1020, input/output interface 1030, and communication interface 1040).
  • the above device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device may also include other components.
  • the above-mentioned device may only include components necessary to implement the solutions of the embodiments of this specification, and does not necessarily include all the components shown in the figure.
  • the electronic device in the above-mentioned embodiments is used to implement the corresponding base station communication coverage method for ultra-high-speed moving objects in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
  • the present disclosure also provides a non-transitory computer-readable storage medium corresponding to the method in any of the above-mentioned embodiments.
  • the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute The base station communication coverage method for an ultra-high-speed moving object as in any of the above embodiments.
  • the computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology.
  • Information may be computer readable instructions, data structures, modules of a program, or other data.
  • Examples of storage media for computers include, but are not limited to, phase-change memory (Phase-change memory, PRAM), static random-access memory (Static Random-Access Memory, SRAM), dynamic random-access memory (Dynamic Random-Access Memory, DRAM) ), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (Electrically Erasable Programmable read only memory, EEPROM), flash memory or other memory technologies, only Compact Disc Read-Only Memory (CD-ROM), Digital Video Disc (DVD) or other optical storage, magnetic cassette, tape magnetic disk storage or other magnetic storage device or any Other non-transmission media that may be used to store information that can be accessed by a computing device.
  • Phase-change memory Phase
  • the computer instructions stored in the storage medium of the above embodiments are used to make the computer execute the base station communication coverage method for ultra-high-speed moving objects as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here repeat.
  • DRAM dynamic RAM

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Abstract

提供一种用于超高速移动物体的基站通信覆盖方法及相关设备，通过摄像头获取目标物体的运动图像(S1)，采用CV算法确定目标物体的当前位置信息和运动信息(S2)，基于当前位置信息、运动信息和基站的位置信息确定到达角度(S3)，基于到达角度确定基站中每个天线的相位信息(S4)，基于相位信息对目标物体进行波束赋形(S5)；基于当前位置信息和运动信息确定目标物体的预测位置(S6)；响应于确定预测位置在基站的通信覆盖范围内，返回获取目标物体的运动图像，响应于确定预测位置不在基站的通信覆盖范围内，则完成对目标物体的通信覆盖(S7)。

Description

用于超高速移动物体的基站通信覆盖方法及相关设备 技术领域
本公开涉及无线通信技术领域，尤其涉及一种用于超高速移动物体的基站通信覆盖方法及相关设备。
背景技术
波束赋形是一种基于天线阵列的信号预处理技术，波束赋形通过调整天线阵列中每个阵元的加权系数产生具有指向性的波束，从而能够获得明显的阵列增益。波束形成的性能增益主要来源于定向通信。为了实现所需的阵列增益从而充分利用波束赋形的优势，发射机和接收机需要协同工作，以确保发射和接收波束的方向正确对齐，这一过程通常被称为波束发现。最常用的基于反馈机制的波束发现方法，包括波束扫描、波束测量、波束确定和波束报告等多个过程。
基站波束赋形技术的高效通信依赖于收发节点的波束对齐，即波束选择过程，而在以物体超高速度移动的背景下则会增加资源开销，同时导致通信连接建立延迟。
发明内容
有鉴于此，本公开的目的在于提出一种用于超高速移动物体的基站通信覆盖方法及相关设备。
基于上述目的，本公开提供了一种用于超高速移动物体的基站通信覆盖方法，包括：
获取目标物体的运动图像；
基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息；
基于所述当前位置信息、所述运动信息和所述基站的位置信息确定所述目标物体与基站天线间的到达角度；
基于所述到达角度通过计算得到所述基站中各天线对应的相位信息；
基于所述相位信息对所述目标物体进行波束赋形；
基于所述当前位置信息和所述运动信息确定所述目标物体的预测位置；
响应于确定所述预测位置在所述基站的通信覆盖范围内，返回所述获取目标物体的运动图像，响应于确定所述预测位置不在所述基站的通信覆盖范围内，则完成对所述目标物体的通信覆盖。
进一步的，所述基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息之前，所述基站通信覆盖方法还包括：
基于所述计算机视觉CV算法对所述目标物体的类别进行检测；
响应于确定所述目标物体属于预设物体类别时，进行所述基于所述运动图像通过所述计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息；
响应于确定所述目标物体不属于预设物体类别时，返回所述获取目标物体的运动图像。
进一步的，所述基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息、运动信息以及基站的位置信息包括：
响应于确定所述运动图像的亮度大于等于预设阈值时，通过第一目标检测算法对所述运动图像进行计算，以得到所述目标物体的当前位置信息、运动信息以及基站的位置信息；
响应于确定所述运动图像的亮度小于所述预设阈值时，通过第二目标检测算法对所述运动图像进行计算，以得到所述目标物体的当前位置信息、运动信息以及基站的位置信息。
进一步的，所述到达角度的计算表达式为
q ab＝arg(s a-s b)
σ a＝(x a，y  a，z a)
s b＝(x b,y b,z b)
其中，θ ab表示到达角度，x a，y a，z a分别表示所述当前位置信息的三维坐标值，x b，y b，z b分别表示所述基站的三维坐标值。
进一步的，所述基于所述到达角度通过计算得到所述基站中各天线对应的相位信息，包括：所述相位信息具体为：
τ l＝(2π/λ)(l-1)(λ/2)cosθ ab
其中，t l表示各天线对应的相位，l＝a，2，...，L，L表示所述基站对所述目标物体进行通信覆盖的天线数量，λ表示所述基站发送信息的波长，相邻所述天线之间的距离间隔为l/2。
进一步的，所述基于所述相位信息对所述目标物体进行波束赋形包括：
基于所述相位信息确定波束赋形向量，基于所述波束赋形向量对所述目标物体进行波束赋形。
进一步的，所述预测位置具体表示为：
σ a-t＝(x a+v t siα，y a+v cosα，z a)
其中，x a，y a，z a分别表示所述当前位置信息的三维坐标值，v表示所述目标物体的运动速度，α表示所述目标物体的速度方向，t表示所述运动图像帧率。
基于同一发明构思，本公开还提供了一种用于超高速移动物体的基站通信覆盖装置，包括：
图像获取模块，被配置为获取目标物体的运动图像；
计算模块，被配置为基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息；
到达角确定模块，被配置为基于所述当前位置信息、所述运动信息和所述基站的位置信息确定所述目标物体与基站天线间的到达角度；
相位信息确定模块，被配置为基于所述到达角度通过计算得到所述基站中各天线对应的相位信息；
波束赋形模块，被配置为基于所述相位信息对所述目标物体进行波束赋形；
位置预测模块，被配置为基于所述当前位置信息和所述运动信息确定所述目标物体的预测位置；
判定模块，被配置为响应于确定所述预测位置在所述基站的通信覆盖范围内，返回所述图像获取模块，响应于确定所述预测位置不在所述基站的通信覆盖范围内，则完成对所述目标物体的通信覆盖。
基于同一发明构思，本公开还提供了一种电子设备，包括存储器、处理器及存储在所述存储器上并可由所述处理器执行的计算机程序，所述处理器在执行所述计算机程序时实现如上所述的基站通信覆盖方法。
基于同一发明构思，本公开还提供了一种非暂态计算机可读存储介质，所述非暂态计算机可读存储介质存储计算机指令，所述计算机指令用于使计算机执行如上所述的基站通信覆盖方法。
从上面所述可以看出，本公开提供的用于超高速移动物体的基站通信覆盖方法及相关设备，通过CV算法确定目标物体的当前位置信息，基于当前位置信息和基站的位置信息确定到达角度，基于到达角度确定基站中每个天线的相位信息。基于该相位信息建立了基站与目标物体之间的通信链路，从而确定波束，完成波束赋形与通信覆盖。本公开的用于超高速移动物体的基站通信覆盖方法基于位置信息进行波束选择，有效缩小波束扫描范围，进一步提高了波束选择的效率和准确性。
附图说明
为了更清楚地说明本公开或相关技术中的技术方案，下面将对实施例或相关技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本公开的实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本公开实施例的用于超高速移动物体的基站通信覆盖方法的流程示意图；
图2为本公开实施例的基站与目标物体的通信场景示意图；
图3为本公开实施例的用于超高速移动物体的基站通信覆盖装置的结构示意图；
图4为本公开实施例的电子设备硬件结构示意图。
具体实施方式
为使本公开的目的、技术方案和优点更加清楚明白，以下结合具体实施例，并参照附图，对本公开进一步详细说明。
需要说明的是，除非另外定义，本公开实施例使用的技术术语或者科学术语应当为本公开所属领域内具有一般技能的人士所理解的通常意义。本公开实施例中使用的“第一”、“第二”以及类似的词语并不表示任何顺序、数量 或者重要性，而只是用来区分不同的组成部分。“包括”或者“包含”等类似的词语意指出现该词前面的元件或者物件涵盖出现在该词后面列举的元件或者物件及其等同，而不排除其他元件或者物件。“连接”或者“相连”等类似的词语并非限定于物理的或者机械的连接，而是可以包括电性的连接，不管是直接的还是间接的。“上”、“下”、“左”、“右”等仅用于表示相对位置关系，当被描述对象的绝对位置改变后，则该相对位置关系也可能相应地改变。
如背景技术所述，基站波束赋形技术的高效通信依赖于收发节点的波束对齐，也就是波束选择过程，而在超高速移动的背景下会增加资源开销以及通信连接建立延迟，基于反馈的波束选择不适合对超高速移动物体进行通信覆盖。因此，位置感知波束选择成为基于反馈的波束选择的可行替代方案。该方法的基础思路是利用接收机的位置来确定发送端对接收端的下行链路波束。本公开公开了一种用于超高速移动物体的基站通信覆盖方法，基于位置信息进行波束选择，缩小波束扫描范围，进一步提高波束选择的效率和准确性。
以下结合附图来详细说明本公开的实施例。
本公开提供了一种用于超高速移动物体的基站通信覆盖方法，参考图1，该方法包括以下几个步骤：
步骤S1、获取目标物体的运动图像。在与目标物体进行通信的基站上部署通信装置，本实施例中的基站为5G基站，通信装置包括摄像头、CV(Computer Vision，计算机视觉)设备、天线、定位设备和相位控制器等等。通过摄像头获取目标物体的运动图像，通过天线、定位设备和相位控制器等对目标物体进行通信覆盖。
步骤S2、基于运动图像通过计算机视觉CV算法得到目标物体的当前位置信息和运动信息以及基站的位置信息。通过设置在基站上的CV设备对运动图像进行计算，以获取目标物体的位置信息和运动信息，在同一坐标系中，同时确定了基站的位置信息，也即得到了目标物体与基站的相对位置关系。
步骤S3、基于当前位置信息、运动信息和基站的位置信息确定目标物体与基站天线间的到达角度。
具体地，到达角度的计算表达式为：
q ab＝arg(s a-s b)
σ a＝(x a，y  a，z a)
s b＝(x b,y b,z b)
其中，θ ab表示到达角度，x a，y a，z a分别表示当前位置信息的三维坐标值，x b，y b，z b分别表示基站的三维坐标值。
步骤S4、基于到达角度通过计算得到基站中各天线对应的相位信息。
具体地，相位表达式具体为：
τ l＝(2π/λ)(l-1)(λ/2)cosθ ab
其中，t l表示各天线对应的相位，l＝1，2，...，L，L表示基站对目标物体进行通信覆盖的天线数量，λ表示基站发送信息的波长，基站中的天线阵列是均匀分布的，相邻天线之间的距离间隔为l/2。
步骤S5、基于相位信息对目标物体进行波束赋形。通过计算得到相位信息后，基站根据相位信息建立与目标物体之间的定向通信链路，从而完成对目标物体的波束赋形。
步骤S6、基于当前位置信息和运动信息确定目标物体的预测位置。
具体地，本实施例中的目标物体为高速运动的物体，例如运行中的高铁，因为高铁的运动轨迹是确定的，因此根据当前位置信息和运动信息可以较为准确的预测下一时刻高铁的位置。
步骤S7、响应于确定预测位置在基站的通信覆盖范围内，返回S1，响应于确定预测位置不在基站的通信覆盖范围内，则完成对目标物体的通信覆盖。
具体地，根据预测位置判断是否需要继续对目标物体进行通信覆盖，如果预测位置包含在通信覆盖范围内，则继续对目标物体进行通信覆盖，如果预测位置未包含在通信覆盖范围内，说明目标物体已经离开通信覆盖范围，即可停止对目标物体进行通信覆盖。
在本实施例中，参考图2，当高铁以高速运动至基站附近时，由于摄像头的视距距离要高于基站的通信距离，因此摄像头将提前监测到高铁，并通过CV算法确定高铁的位置和运动速度，同时高铁的行驶方向和轨迹是确定的，可根据高铁当前的位置信息和运动信息估计高铁在下一时刻的位置。若下一时刻的位置在基站的通信范围内，则继续对高铁进行通信覆盖，若下一时刻的位置不在基站的通信范围内，则完成对高铁的通信覆盖。本实施例的通信覆盖方法能够缩小波束扫描预定方向的搜索范围，提高波束成型的通信 效率。
在一些实施例中，在步骤S2之前还包括：基于计算机视觉CV算法对目标物体的类别进行检测，响应于确定目标物体属于预设物体类别时，进行步骤S2，响应于确定目标物体不属于预设物体类别时，返回步骤S1。
具体地，通过CV设备检测到目标物体不属于预设物体类别时，无需对采集到的运动图像进行计算，当确定目标物体为预设物体类别时，则进行下一步CV计算。本实施例中，预设物体类别为高铁，当CV设备检测到目标物体为高铁时，对高铁的运动图像进行计算，进一步确定高铁的当前位置信息、运动信息以及基站的位置信息。
在一些实施例中，基于运动图像通过计算机视觉CV算法得到目标物体的当前位置信息、运动信息以及基站的位置信息包括：
响应于确定运动图像的亮度大于等于预设阈值时，通过第一目标检测算法对运动图像进行计算，以得到目标物体的当前位置信息、运动信息以及基站的位置信息；
响应于确定运动图像的亮度小于预设阈值时，通过第二目标检测算法对运动图像进行计算，以得到目标物体的当前位置信息、运动信息以及基站的位置信息。
具体地，在摄像头采集运动图像时，由于白天和夜晚光线差别较大，导致获取到的运动图像亮度不同。为了基于运动图像得到准确的位置信息和运动信息，针对不同亮度的运动图像，所需的CV算法也不相同。因此，在白天和夜晚进行运动图像获取时，需要不同的目标检测方法对运动图像进行计算。对于在白天获取的运动图像，通过第一目标检测算法对其进行计算，本实施例中的第一目标检测算法引用专利申请公布号为CN111460919A的目标检测及距离估计方法。对于在夜晚获取的运动图像，通过第二目标检测算法对其进行计算，本实施例中的第二目标检测算法引用专利申请公布号为CN100546380C的夜间目标检测和跟踪方法。
另外，若因为恶劣天气、能见度较低导致运动图像不清晰，致使CV算法的识别精度小于预设阈值，则需要基站通过现有的波束赋形方法对目标物体进行通信覆盖，也即通过基于反馈的波束选择方法对目标物体进行波束赋形，此种波束赋形的具体方法属于现有技术，此处不再赘述。
在一些实施例中，基于相位信息对目标物体进行波束赋形，包括：基于相位信息确定波束赋形向量，基于波束赋形向量对目标物体进行波束赋形。
具体地，波束赋形向量具体为：
W＝[w 1，w 2，…，w l，…w L]
Figure PCTCN2022096979-appb-000001
其中，w l表示第l根天线的权值，l＝1，2，...，L，A l表示波束赋形运算的响应幅度，j表示虚数单位。根据计算得到的波束赋形向量，基站对目标物体进行波束赋形。
在一些实施例中，预测位置具体表示为：
σ a-t＝(x a+v t sinα，y a+v cosα，z a)
其中，x a，y a，z a分别表示当前位置信息的三维坐标值，v表示目标物体的运动速度，α表示目标物体的速度方向，t表示运动图像帧率。
需要说明的是，本公开实施例的方法可以由单个设备执行，例如一台计算机或服务器等。本实施例的方法也可以应用于分布式场景下，由多台设备相互配合来完成。在这种分布式场景的情况下，这多台设备中的一台设备可以只执行本公开实施例的方法中的某一个或多个步骤，这多台设备相互之间会进行交互以完成所述的基站通信覆盖方法。
需要说明的是，上述对本公开的一些实施例进行了描述。其它实施例在所附权利要求书的范围内。在一些情况下，在权利要求书中记载的动作或步骤可以按照不同于上述实施例中的顺序来执行并且仍然可以实现期望的结果。另外，在附图中描绘的过程不一定要求示出的特定顺序或者连续顺序才能实现期望的结果。在某些实施方式中，多任务处理和并行处理也是可以的或者可能是有利的。
基于同一发明构思，与上述任意实施例方法相对应的，本公开还提供了一种用于超高速移动物体的基站通信覆盖装置。
参考图3，用于超高速移动物体的基站通信覆盖装置，包括：
图像获取模块301，被配置为获取目标物体的运动图像；
计算模块302，被配置为基于运动图像通过计算机视觉CV算法得到目标 物体的当前位置信息和运动信息以及基站的位置信息；
到达角确定模块303，被配置为基于当前位置信息、运动信息和基站的位置信息确定目标物体与基站天线间的到达角度；
相位信息确定模块304，被配置为基于到达角度通过计算得到基站中各天线对应的相位信息；
波束赋形模块305，被配置为基于相位信息对目标物体进行波束赋形；
位置预测模块306，被配置为基于当前位置信息和运动信息确定目标物体的预测位置；
判定模块307，被配置为响应于确定预测位置在基站与目标物体的通信覆盖范围内，返回图像获取模块301，响应于确定预测位置不在基站与目标物体的通信覆盖范围内，则完成对目标物体的通信覆盖。
在一些实施例中，还包括类别确定模块308，被配置为基于计算机视觉CV算法对目标物体的类别进行检测，
响应于确定目标物体属于预设物体类别时，执行计算模块302，
响应于确定目标物体不属于预设物体类别时，返回图像获取模块301。
在一些实施例中，计算模块302具体被配置为，基于运动图像通过计算机视觉CV算法得到目标物体的当前位置信息、运动信息以及基站的位置信息包括：
响应于确定运动图像的亮度大于等于预设阈值时，通过第一目标检测算法对运动图像进行计算，以得到目标物体的当前位置信息、运动信息以及基站的位置信息；
响应于确定运动图像的亮度小于预设阈值时，通过第二目标检测算法对运动图像进行计算，以得到目标物体的当前位置信息、运动信息以及基站的位置信息。
在一些实施例中，到达角确定模块303，具体被配置为到达角度的计算表达式为：
q ab＝arg(s a-s b)
σ a＝(x a，y a，z a)
s b＝(x b,y b,z b)
其中，θ ab表示到达角度，x a，y a，z a分别表示当前位置信息的三维坐标值， x b，y b，z b分别表示基站的三维坐标值。
在一些实施例中，相位信息确定模块304，具体被配置为基于到达角度通过计算得到基站中各天线对应的相位信息包括：相位信息具体为：
τ l＝(2π/λ)(l-1)(λ/2)cosθ ab
其中，t l表示各天线对应的相位，l＝1，2，...，L，L表示基站对目标物体进行通信覆盖的天线数量，λ表示基站发送信息的波长，相邻天线之间的距离间隔为l/2。
在一些实施例中，波束赋形模块305，具体被配置为基于相位信息对目标物体进行波束赋形，包括：
基于相位信息确定波束赋形向量，基于波束赋形向量对目标物体进行波束赋形。
在一些实施例中，位置预测模块306，具体被配置为预测位置具体表示为：
σ a-t＝(x a+v t sinα，y a+v cosα，z a)
其中，x a，y a，z a分别表示当前位置信息的三维坐标值，v表示目标物体的运动速度，α表示目标物体的速度方向，t表示运动图像帧率。
为了描述的方便，描述以上装置时以功能分为各种模块分别描述。当然，在实施本公开时可以把各模块的功能在同一个或多个软件和/或硬件中实现。
上述实施例的装置用于实现前述任一实施例中相应的用于超高速移动物体的基站通信覆盖方法，并且具有相应的方法实施例的有益效果，在此不再赘述。
基于同一发明构思，与上述任意实施例方法相对应的，本公开还提供了一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，处理器执行程序时实现上任意一实施例的用于超高速移动物体的基站通信覆盖方法。
图4示出了本实施例所提供的一种更为具体的电子设备硬件结构示意图，该设备可以包括：处理器1010、存储器1020、输入/输出接口1030、通信接口1040和总线1050。其中处理器1010、存储器1020、输入/输出接口1030和通信接口1040通过总线1050实现彼此之间在设备内部的通信连接。
处理器1010可以采用通用的CPU(Central Processing Unit，中央处理器)、 微处理器、应用专用集成电路(Application Specific Integrated Circuit，ASIC)、或者一个或多个集成电路等方式实现，用于执行相关程序，以实现本说明书实施例所提供的技术方案。
存储器1020可以采用ROM(Read Only Memory，只读存储器)、RAM(Random Access Memory，随机存取存储器)、静态存储设备，动态存储设备等形式实现。存储器1020可以存储操作***和其他应用程序，在通过软件或者固件来实现本说明书实施例所提供的技术方案时，相关的程序代码保存在存储器1020中，并由处理器1010来调用执行。
输入/输出接口1030用于连接输入/输出模块，以实现信息输入及输出。输入输出/模块可以作为组件配置在设备中(图中未示出)，也可以外接于设备以提供相应功能。其中输入设备可以包括键盘、鼠标、触摸屏、麦克风、各类传感器等，输出设备可以包括显示器、扬声器、振动器、指示灯等。
通信接口1040用于连接通信模块(图中未示出)，以实现本设备与其他设备的通信交互。其中通信模块可以通过有线方式(例如USB、网线等)实现通信，也可以通过无线方式(例如移动网络、WIFI、蓝牙等)实现通信。
总线1050包括一通路，在设备的各个组件(例如处理器1010、存储器1020、输入/输出接口1030和通信接口1040)之间传输信息。
需要说明的是，尽管上述设备仅示出了处理器1010、存储器1020、输入/输出接口1030、通信接口1040以及总线1050，但是在具体实施过程中，该设备还可以包括实现正常运行所必需的其他组件。此外，本领域的技术人员可以理解的是，上述设备中也可以仅包含实现本说明书实施例方案所必需的组件，而不必包含图中所示的全部组件。
上述实施例的电子设备用于实现前述任一实施例中相应的用于超高速移动物体的基站通信覆盖方法，并且具有相应的方法实施例的有益效果，在此不再赘述。
基于同一发明构思，与上述任意实施例方法相对应的，本公开还提供了一种非暂态计算机可读存储介质，非暂态计算机可读存储介质存储计算机指令，计算机指令用于使计算机执行如上任一实施例的用于超高速移动物体的基站通信覆盖方法。
本实施例的计算机可读介质包括永久性和非永久性、可移动和非可移动 媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(Phase-change memory，PRAM)、静态随机存取存储器(Static Random-Access Memory，SRAM)、动态随机存取存储器(Dynamic Random Access Memory，DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(Electrically Erasable Programmable read only memory，EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(Compact Disc Read-Only Memory，CD-ROM)、数字多功能光盘(Digital Video Disc，DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。
上述实施例的存储介质存储的计算机指令用于使计算机执行如上任一实施例所述的用于超高速移动物体的基站通信覆盖方法，并且具有相应的方法实施例的有益效果，在此不再赘述。
所属领域的普通技术人员应当理解：以上任何实施例的讨论仅为示例性的，并非旨在暗示本公开的范围(包括权利要求)被限于这些例子；在本公开的思路下，以上实施例或者不同实施例中的技术特征之间也可以进行组合，步骤可以以任意顺序实现，并存在如上所述的本公开实施例的不同方面的许多其它变化，为了简明它们没有在细节中提供。
另外，为简化说明和讨论，并且为了不会使本公开实施例难以理解，在所提供的附图中可以示出或可以不示出与集成电路(IC)芯片和其它部件的公知的电源/接地连接。此外，可以以框图的形式示出装置，以便避免使本公开实施例难以理解，并且这也考虑了以下事实，即关于这些框图装置的实施方式的细节是高度取决于将要实施本公开实施例的平台的(即，这些细节应当完全处于本领域技术人员的理解范围内)。在阐述了具体细节(例如，电路)以描述本公开的示例性实施例的情况下，对本领域技术人员来说显而易见的是，可以在没有这些具体细节的情况下或者这些具体细节有变化的情况下实施本公开实施例。因此，这些描述应被认为是说明性的而不是限制性的。
尽管已经结合了本公开的具体实施例对本公开进行了描述，但是根据前面的描述，这些实施例的很多替换、修改和变型对本领域普通技术人员来说 将是显而易见的。例如，其它存储器架构(例如，动态RAM(DRAM))可以使用所讨论的实施例。
本公开实施例旨在涵盖落入所附权利要求的宽泛范围之内的所有这样的替换、修改和变型。因此，凡在本公开实施例的精神和原则之内，所做的任何省略、修改、等同替换、改进等，均应包含在本公开的保护范围之内。

Claims (10)

  1. 一种用于超高速移动物体的基站通信覆盖方法，其特征在于，包括：
    获取目标物体的运动图像(S1)；
    基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息(S2)；
    基于所述当前位置信息、所述运动信息和所述基站的位置信息确定所述目标物体与基站天线间的到达角度(S3)；
    基于所述到达角度通过计算得到所述基站中各天线对应的相位信息(S4)；
    基于所述相位信息对所述目标物体进行波束赋形(S5)；
    基于所述当前位置信息和所述运动信息确定所述目标物体的预测位置(S6)；
    响应于确定所述预测位置在所述基站的通信覆盖范围内，返回所述获取目标物体的运动图像，响应于确定所述预测位置不在所述基站的通信覆盖范围内，则完成对所述目标物体的通信覆盖(S7)。
  2. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息之前，所述基站通信覆盖方法还包括：
    基于所述计算机视觉CV算法对所述目标物体的类别进行检测；
    响应于确定所述目标物体属于预设物体类别时，进行所述基于所述运动图像通过所述计算机视觉CV算法得到所述目标物体的当前位置信息和运动信息以及基站的位置信息；
    响应于确定所述目标物体不属于预设物体类别时，返回所述获取目标物体的运动图像。
  3. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息、运动信息以及基站的位置信息包括：
    响应于确定所述运动图像的亮度大于等于预设阈值时，通过第一目标检 测算法对所述运动图像进行计算，以得到所述目标物体的当前位置信息、运动信息以及基站的位置信息；
    响应于确定所述运动图像的亮度小于所述预设阈值时，通过第二目标检测算法对所述运动图像进行计算，以得到所述目标物体的当前位置信息、运动信息以及基站的位置信息。
  4. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述到达角度的计算表达式为：
    q ab＝arg(s a-s b)
    σ a＝(x a，y a，z a)
    s b＝(x b,y b,z b)
    其中，θ ab表示到达角度，x a，y a，z a分别表示所述当前位置信息的三维坐标值，x b，y b，z b分别表示所述基站的三维坐标值。
  5. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述基于所述到达角度通过计算得到所述基站中各天线对应的相位信息包括：所述相位信息具体为：
    τ l＝(2π/λ)(l-1)(λ/2)cosθ ab
    其中，t l表示各天线对应的相位，l＝1，2，...，L，L表示所述基站对所述目标物体进行通信覆盖的天线数量，λ表示所述基站发送信息的波长，相邻所述天线之间的距离间隔为l/2。
  6. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述基于所述相位信息对所述目标物体进行波束赋形包括：
    基于所述相位信息确定波束赋形向量，基于所述波束赋形向量对所述目标物体进行波束赋形。
  7. 根据权利要求1所述的基站通信覆盖方法，其特征在于，所述预测位置具体表示为：
    σ a-t＝(x a+v t sinα，y a+v cosα，z a)
    其中，x a，y a，z a分别表示所述当前位置信息的三维坐标值，v表示所述目标物体的运动速度，α表示所述目标物体的速度方向，t表示所述运动图像帧率。
  8. 一种用于超高速移动物体的基站通信覆盖装置，其特征在于，包括：
    图像获取模块(301)，被配置为获取目标物体的运动图像；
    计算模块(302)，被配置为基于所述运动图像通过计算机视觉CV算法得到所述目标物体的当前位置信息、运动信息以及基站的位置信息；
    到达角确定模块(303)，被配置为基于所述当前位置信息、所述运动信息和所述基站的位置信息确定所述目标物体与基站天线间的到达角度；
    相位信息确定模块(304)，被配置为基于所述到达角度通过计算得到所述基站中各天线对应的相位信息；
    波束赋形模块(305)，被配置为基于所述相位信息对所述目标物体进行波束赋形；
    位置预测模块(306)，被配置为基于所述当前位置信息和所述运动信息确定所述目标物体的预测位置；
    判定模块(307)，被配置为响应于确定所述预测位置在所述基站的通信覆盖范围内，返回所述图像获取模块(301)，响应于确定所述预测位置不在所述基站的通信覆盖范围内，则完成对所述目标物体的通信覆盖。
  9. 一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现如权利要求1至7任意一项所述的基站通信覆盖方法。
  10. 一种非暂态计算机可读存储介质，所述非暂态计算机可读存储介质存储计算机指令，其特征在于，所述计算机指令用于使计算机执行权利要求1至7任意一项所述的基站通信覆盖方法。
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