CN112512011B - Method, device and system for positioning vehicle terminal in 5G networking automatic driving - Google Patents

Method, device and system for positioning vehicle terminal in 5G networking automatic driving Download PDF

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CN112512011B
CN112512011B CN202011287479.3A CN202011287479A CN112512011B CN 112512011 B CN112512011 B CN 112512011B CN 202011287479 A CN202011287479 A CN 202011287479A CN 112512011 B CN112512011 B CN 112512011B
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arrival
vehicle terminal
base station
time
vehicle
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CN112512011A (en
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王鲁晗
李德鑫
初星河
王刚
傅彬
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Zhiyou Open Source Communication Research Institute Beijing Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/025—Services making use of location information using location based information parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/003—Locating users or terminals or network equipment for network management purposes, e.g. mobility management locating network equipment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination

Abstract

The embodiment of the disclosure discloses a method, a device and a system for positioning a vehicle terminal in 5G networking automatic driving, wherein the method comprises the following steps: respectively receiving ranging signals from a plurality of vehicle terminals by using an antenna array on a base station, and generating a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; constructing an objective function by using the signal matrix, wherein the objective function is used for estimating the arrival time and the arrival angle of the ranging signal from the vehicle terminal to the base station; solving the arrival angle and the arrival time when the product of a guide vector formed by the arrival angle from each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using an objective function in a continuous iteration mode; receiving a channel parameter transmission signal from a vehicle terminal using an antenna array; time offsets and positions of the plurality of vehicle terminals are obtained based on the arrival angles and arrival times of the vehicle terminals.

Description

Method, device and system for positioning vehicle terminal in 5G networking automatic driving
Technical Field
The disclosure relates to the technical field of computers, in particular to a method, a device and a system for positioning a vehicle terminal in 5G networking automatic driving.
Background
The development of the automatic driving technology has extremely high requirements on the positioning accuracy of the vehicle, the 5G communication technology is gradually popularized, and the novel technology and network framework are used, including a novel full duplex mode, Massive MIMO, Flexible-OFDM, millimeter wave communication and an indoor base station. The technologies enable 5G communication to have higher data transmission rate (10Gbit/s), lower transmission delay (1ms) and larger connectable number of terminals (1000000 connections/km)2). Large bandwidth will promote the Time of Arrival (ToA) basisInter) distance resolution of the localization technique; massive MIMO will improve the angular resolution of AoA (Angle of Arrival) based positioning techniques; the low transmission delay can improve the real-time performance of the positioning data and meet the requirement of automatic driving on low delay; the presence of indoor base stations can provide great support for indoor positioning of vehicles. 5G-based positioning technology can be used in vehicle positioning systems in autonomous driving.
Typical positioning techniques in the prior art include GPS positioning techniques and base station positioning techniques. The GPS positioning technology is a global positioning system technology in which a positioning device can be obtained by receiving radio waves from satellites. The global positioning system includes a fixed station and a mobile station. The fixed station is set at a fixed reference point, and the mobile station performs positioning while moving successively between a large number of measurement points, obtaining relative position coordinates with respect to the fixed station. In the base station positioning technology, a terminal firstly sends PRS signals to a service base station and a plurality of cooperative base stations; then all cooperative base stations execute PRS detection and TOA measurement; finally, the serving base station performs a positioning estimation based on the TOA measurement result. However, the GPS positioning technology has blind areas in busy cities, poor weather conditions and indoor areas; and the positioning precision of the base station positioning technology under 2G-4G networks is low, and the transmission delay is large.
Disclosure of Invention
The embodiment of the disclosure provides a method, a device and a system for positioning a vehicle terminal in 5G networking automatic driving.
In a first aspect, an embodiment of the present disclosure provides a method for positioning a vehicle terminal in 5G networking automatic driving, including:
respectively receiving ranging signals from a plurality of vehicle terminals by using an antenna array on a base station, and generating a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
constructing an objective function using the signal matrix, the objective function being used to estimate arrival times and arrival angles of the ranging signals from the vehicle terminals to the base station, and the objective function being used to solve for the arrival times when steering vectors of the arrival angles and estimated vectors of the arrival times are maximum;
solving the arrival angle and the arrival time when the product of a steering vector formed by the arrival angle from each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using the objective function in a continuous iteration mode;
receiving a channel parameter transmission signal from the vehicle terminal using the antenna array; the channel parameter transmission signal comprises arrival angles and arrival times corresponding to other vehicle terminals estimated by the vehicle terminals;
obtaining time offsets and locations of a plurality of the vehicle terminals based on the angle of arrival and time of arrival of the vehicle terminals.
Further, the ranging signal includes a signature signal transmitted by the vehicle terminal, the signature signal being generated by the vehicle terminal through a pseudo random code sequence.
Further, after solving, by using the objective function in an iterative manner, the arrival angle and the arrival time at which a product of a steering vector formed by the arrival angle of each vehicle terminal to the base station and an estimated vector formed by the arrival time is maximum, the method further includes:
generating a channel parameter transmission signal, the channel parameter transmission signal comprising the angle of arrival and the time of arrival;
broadcasting the channel parameter transmission signal.
Further, obtaining time offsets and locations of a plurality of the vehicle terminals based on the angle of arrival and time of arrival of the vehicle terminals comprises:
generating a channel parameter vector based on the arrival time and the arrival angle of the vehicle terminal; the channel parameter vector comprises an arrival angle from each vehicle terminal to the base station, arrival time between every two vehicle terminals, channel gain between every two vehicle terminals, arrival time from the vehicle terminals to the base station and channel gain from the vehicle terminals to the base station;
and acquiring the clock offset and the position of each vehicle terminal according to the channel parameter vector.
Further, acquiring the clock offset and the position of each vehicle terminal according to the channel parameter vector includes:
determining the distance between the base station and the vehicle terminal according to the arrival time from the base station to the vehicle terminal and the arrival time from the vehicle terminal to the base station;
determining a time offset of the vehicle terminal based on a distance of the base station from the vehicle terminal, an arrival time of the base station to the vehicle terminal, and the time offset of the base station;
determining a location of the vehicle terminal based on the time offset of the vehicle terminal, the arrival time and the arrival angle of the base station to the vehicle terminal.
Further, obtaining time offsets and locations of a plurality of the vehicle terminals based on the angle of arrival and time of arrival of the vehicle terminals comprises:
based on the arrival angle and arrival time of the vehicle terminal, constructing a convex optimization model of the distance from the vehicle terminal to the base station and the time offset of the vehicle terminal by using a semi-positive planning method, solving the convex optimization model to obtain a preliminary solution of the time offset of the vehicle terminal, and obtaining a preliminary solution of the position of the vehicle terminal based on the preliminary solution of the time offset;
and constructing a non-convex optimization model of the Fisher-Tropsch information matrix about the time offset preliminary solution and the position preliminary solution, and solving the non-convex optimization model to obtain a target solution of the time offset and the position.
In a second aspect, an embodiment of the present invention provides a system for locating a vehicle terminal in 5G networking automatic driving, including: a plurality of vehicle terminals and base stations;
the vehicle terminal sends signature signals to other vehicle terminals and the base station;
the vehicle terminal also receives a ranging signal from the other vehicle terminal, wherein the ranging signal corresponds to the signature signal sent by the other vehicle terminal;
the vehicle terminal estimates a first arrival angle and a first arrival time from the other vehicle terminal to the vehicle terminal according to the ranging signal, generates a channel parameter sending signal based on the first arrival angle and the first arrival time, and sends the channel parameter sending signal to the other vehicle terminal and the base station;
the base station receives ranging signals from a plurality of the vehicle terminals, and estimates a second arrival angle and a second arrival time of the vehicle terminals to the base station based on the ranging signals;
the base station generates a channel parameter sending signal based on the second arrival angle and the second arrival time, and sends the channel parameter sending signal to the vehicle terminal;
the base station receives a channel parameter transmission signal from the vehicle terminal, the channel parameter transmission signal corresponding to the channel parameter transmission signal, the base station calculates a time offset from the vehicle terminal to the base station and a position of the vehicle terminal based on the channel parameter transmission signals received from the plurality of vehicle terminals.
In a third aspect, an embodiment of the present invention provides a positioning device for a vehicle terminal in 5G networking automatic driving, where the positioning device includes:
the first receiving module is configured to receive ranging signals from a plurality of vehicle terminals by using an antenna array on a base station respectively, and generate a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
a construction module configured to construct an objective function using the signal matrix, the objective function being used to estimate arrival times and arrival angles of the ranging signals from the vehicle terminals to the base station, and the objective function being used to solve for the arrival time when a steering vector of the arrival angles and an estimated vector of the arrival times are maximum;
a solving module configured to solve the arrival angle and the arrival time when a product of a steering vector formed by the arrival angle of each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using the objective function in an iterative manner;
a second receiving module configured to receive a channel parameter transmission signal from the vehicle terminal using the antenna array; the channel parameter transmission signal comprises arrival angles and arrival times corresponding to other vehicle terminals estimated by the vehicle terminals;
an obtaining module configured to obtain time offsets and positions of a plurality of the vehicle terminals based on the arrival angles and arrival times of the vehicle terminals.
The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-described functions.
In one possible design, the apparatus includes a structure including a memory for storing one or more computer instructions that enable the apparatus to perform the method, and a processor configured to execute the computer instructions stored in the memory. The apparatus may also include a communication interface for the apparatus to communicate with other devices or a communication network.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory and a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method of any of the above aspects.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for use by any of the above-mentioned apparatuses, including computer instructions for performing the method according to any of the above-mentioned aspects.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the automatic driving vehicle is used as a mobile terminal to access a 5G network, a single base station is used as an anchor point, a plurality of vehicle terminals are used as agents, and a single base station positioning and synchronizing scheme using full duplex as a communication mode is provided for a line-of-sight scene. The embodiment of the disclosure provides an accurate channel estimation algorithm to obtain the arrival angle and arrival time of a terminal, and further develops a positioning and synchronization algorithm on the basis to obtain the position and clock offset of a vehicle terminal, thereby realizing high-precision positioning of a vehicle in 5G networking automatic driving.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
fig. 1 shows a flowchart of a method for locating a vehicle terminal in 5G internet autonomous driving according to an embodiment of the present disclosure;
FIG. 2 illustrates a schematic diagram of an application scenario with a single base station and two vehicle terminals according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a channel parameter estimation method for estimating channel parameters based on ranging signals and a solving method for clock offset and position by a vehicle terminal and a base station according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram showing a frame structure of a positioning system of a vehicle terminal in 5G networking automatic driving according to an embodiment of the disclosure;
FIG. 5 illustrates a system framework diagram of a vehicle terminal or base station according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device suitable for implementing a method for positioning a vehicle terminal in 5G internet autonomous driving according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The disclosure provides a method for positioning a vehicle terminal in 5G networking automatic driving. The automatic driving vehicle is used as a mobile terminal to access a 5G network, a single base station is used as an anchor point, a plurality of vehicle terminals are used as agents, and a single base station positioning and synchronizing scheme using full duplex as a communication mode is provided for a line-of-sight scene. The embodiment of the disclosure provides an accurate channel estimation algorithm to obtain the arrival angle and arrival time of a terminal, and further develops a positioning and synchronization algorithm on the basis to obtain the position and clock offset of a vehicle terminal, thereby realizing high-precision positioning of a vehicle in 5G networking automatic driving.
The details of the embodiments of the present disclosure are described in detail below with reference to specific embodiments.
Fig. 1 shows a flowchart of a method for locating a vehicle terminal in 5G internet autonomous driving according to an embodiment of the present disclosure. As shown in fig. 1, the method for positioning the vehicle terminal in the 5G internet automatic driving includes the following steps:
in step S101, receiving ranging signals from a plurality of vehicle terminals respectively using an antenna array on a base station, and generating a signal matrix including the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
in step S102, constructing an objective function by using the signal matrix, wherein the objective function is used for estimating arrival time and arrival angle of the ranging signal from the vehicle terminal to the base station, and the objective function is used for solving the arrival time when a steering vector of the arrival angle and an estimated vector of the arrival time are maximum;
in step S103, by using the objective function in a continuous iterative manner, solving the arrival angle and the arrival time when a product of a steering vector formed by the arrival angle from each vehicle terminal to the base station and an estimated vector formed by the arrival time is maximum;
receiving a channel parameter transmission signal from the vehicle terminal using the antenna array in step S104; the channel parameter transmission signal comprises arrival angles and arrival times corresponding to other vehicle terminals estimated by the vehicle terminals;
in step S105, time offsets and positions of a plurality of the vehicle terminals are obtained based on the arrival angles and arrival times of the vehicle terminals.
In this embodiment, N may be included in the vehicle terminal networkaEach vehicle terminal is configured with a full-duplex radio, and at least one base station is configured with an ULA (Uniform Linear Array) of M elements, wherein the distance between the antennas is d. The base station can be called as an anchor point, the anchor point and the vehicle terminal accessed to the anchor point are represented by nodes, a node 0 represents the base station, and other nodes represent vehicle terminals. It is assumed that the vehicle terminals have frame synchronization with unknown and small clock skew. The index set of all vehicle terminals is defined as
Figure BDA0002782838560000071
The index set of the neighbors of node i (i.e., all nodes except node i) is defined as
Figure BDA0002782838560000076
Clock offset and the position of node i are respectively determined by
Figure BDA0002782838560000072
And
Figure BDA0002782838560000073
and (4) showing. Assuming no loss of generality, the clock offset and the position of the base station are respectively
Figure BDA0002782838560000074
And
Figure BDA0002782838560000075
under line-of-sight conditions, each vehicle terminal communicates with its neighbors by means of full-duplex radio, and the base station receives the signals transmitted from the vehicle terminals through its antenna array. In some embodiments, there are two types of transmission frames: measurement frames and digital response frames. The measurement frame is used to transmit a ranging signal, and the digital response frame is used to transmit channel parameters measured through channel estimation.
The measurement frame and the digital response frame are described separately below.
Measurement frame
In the measurement frame, each vehicle terminal i first generates a signature signal s by means of a pseudo-random code sequencei(t), for example, pseudo-random code sequences can employ M-sequences and Gold sequences, which have good auto-correlation and cross-correlation properties. Under the condition of frame synchronization, each vehicle terminal broadcasts a signature signal to other nodes in the network according to its local time, the base station receives the broadcast signature signal transmitted from the vehicle terminal, and the vehicle terminal receives the broadcast signature signal transmitted from other vehicle terminals. Let niIs a neighbor node set of a vehicle terminal i, wherein i belongs to naThe signal received by the vehicle terminal i is
ri(t)＝ui(t)+wi(t),t∈[0,Tf]
Wherein
Figure BDA0002782838560000081
wi(t) represents the observed noise after self-interference (SI) cancellation, modelable as complex additive white gaussian noise; t isfIs the duration of one frame, alphaijAnd τijRespectively representing the channel gain and the arrival time (according to the clock of node i) of the signal transmitted from node j to node i, the arrival time tauijDistance dijClock offset ζ of ith nodejAnd clock offset ζ of jth nodejThe relationship of (c) can be written as:
Figure BDA0002782838560000082
wherein c represents the propagation velocity of light, then
Figure BDA0002782838560000083
Representing the distance between nodes i and j. All vehicle terminals are frame-synchronized and the entire signature signal si(t) falls within one frame interval.
Similarly, the signal received by the antenna array at the base station, i.e. the signal after the measurement frame is received by the antenna array at the base station, can be represented as follows:
Figure BDA0002782838560000084
Figure BDA0002782838560000085
wherein the content of the first and second substances,
Figure BDA0002782838560000086
in (1)
Figure BDA0002782838560000087
Represents the observed Noise modeled as complex AWGN (Additive White Gaussian Noise), iota is a complex unit, fcIs the carrier frequency of the carrier wave,
Figure BDA0002782838560000091
is the angle of arrival from node j to the base station antenna array, M represents the total number of antennas in the anchor antenna array, viAnd (t) represents a time domain signal received by the ith antenna, and the arrival angle of the measurement signal can be calculated according to the signals (including the time domain signal received by each antenna) received by the whole antenna array. From v abovei(t) As can be seen, the signal received by the base station and the arrival time tau0jAnd angle of arrival phijCorrelation, and therefore the time of arrival and angle of arrival can be calculated from the received signal by a channel estimation algorithm.
(II) digital response frame
In the digital response frame, each vehicle terminal i (i ∈ n)a) First based on the received signal ri(t) (i.e. the signature signal transmitted by other vehicle terminal reaches vehicle terminal i after propagating through the channel, the signal is received by the antenna array of vehicle terminal i) estimates the channel parameters (i.e. the arrival time and the channel gain) of other vehicle terminal, and then generates a digital response frame containing enough statistical information for estimating the channel parameters of the vehicle terminal transmitting the signature signal. At the same time, the base station receives the signal r0(t) estimating channel parameters of the vehicle terminal. Then, each vehicle terminal i broadcasts the digital response frame it generates to other nodes, and the base station and the vehicle terminal receive broadcast signals from its neighboring vehicle terminals.
In this embodiment, each vehicle terminal transmits a measurement frame including a signature signal s to surrounding vehicles and a base stationi(t) of (d). Each vehicle terminal and the base station receive a measurement frame from the surrounding vehicle terminals, and the measurement frame comprises a ranging signal ri(t), i.e. a signature signal s corresponding to the senderi(t)。
Each vehicle terminal and the base station can estimate initial estimated values of the arrival angle and the arrival time of the signal arriving from other vehicle terminals locally by using a channel estimation algorithm from the received ranging signal, that is, the initial estimated values are obtained in the steps 101 to 103, and the initial estimated values respectively include the initial estimated value of the arrival angle and the initial estimated value of the arrival time.
After each vehicle terminal and the base station obtain the initial estimation value, the initial estimation value is put into a digital response frame, and then the digital response frame is broadcasted to the surrounding vehicle terminals and the surrounding base stations, namely the vehicle terminals and the surrounding base stations receive the initial estimation values of the arrival angles and the arrival times estimated by other vehicle terminals from other surrounding vehicle terminals, and meanwhile, the base stations generate the digital response frame according to the locally estimated initial estimation value and then send the digital response frame to the surrounding vehicle terminals. The vehicle terminal also receives preliminary estimates of the arrival angle and arrival time with other vehicle terminals sent by the base station.
Through the signal transmission, the base station obtains the initial estimation values of the arrival angle and the arrival time of the signals from other vehicle terminals to the base station, and also obtains the initial estimation values of the arrival angle and the arrival time between the other vehicle terminals. Meanwhile, each vehicle terminal obtains preliminary estimated values of the arrival angle and arrival time from the other vehicle terminals to the local, preliminary estimated values of the arrival angle and arrival time from the other vehicles to the base station, and preliminary estimated values of the arrival angle and arrival time between the other vehicles.
At the base station, the clock offset and the position of each vehicle terminal relative to the base station can be obtained by calculation based on a semi-positive planning method by using preliminary estimated values of arrival angles and arrival times among all nodes (including the vehicle terminal and the base station) in the vehicle terminal network.
The following describes an embodiment of the present disclosure by taking an example in which a vehicle terminal network includes two vehicle terminals.
Fig. 2 shows a schematic diagram of an application scenario with a single base station and two vehicle terminals according to an embodiment of the present disclosure. As shown in FIG. 2, from the measurement frame, the vehicle terminals ((i.e., vehicle terminals i and j)) may be based on the formula ri(t)＝ui(t)+wi(t),t∈[0,Tf]Estimating a parameter tauijAnd τjiThe base station canAccording to the formula
Figure BDA0002782838560000101
Estimating parameters
Figure BDA0002782838560000102
. Then, from the digital response frame, the base station can estimate the distance d between the vehicle terminals i and jij＝c(τij+τji) And/2, the distance difference between the vehicle terminals i and j to the base station is delta dij＝c(τ0j-τ0i-(τij-τji)/2). From these estimates, it can be demonstrated that the position of the vehicle terminal and the clock offset can be determined after algebraic calculations are performed. Finally, due to N in the networkaThe individual vehicle terminals can be separated into different pairs of vehicle terminals, and the above example is explained for only one pair of vehicle terminals, so that by dividing NaAfter the vehicle terminal is decomposed into a plurality of vehicle terminal pairs, the position and the clock offset of each vehicle terminal can be obtained by calculation by adopting the example.
In an optional implementation manner of this embodiment, after the step S103 of solving, by using the objective function in an iterative manner, the arrival angle and the arrival time when a product of a steering vector formed by the arrival angle of each vehicle terminal to the base station and an estimated vector formed by the arrival time is maximum, the method further includes the following steps:
generating a channel parameter transmission signal, the channel parameter transmission signal comprising the angle of arrival and the time of arrival;
broadcasting the channel parameter transmission signal.
In this optional implementation manner, as described above, each vehicle terminal and the base station may estimate an arrival angle and an arrival time from other vehicle terminals to the local area based on the received ranging signal, that is, the content in the measurement frame, and based on the arrival angle and the arrival time, the vehicle terminal and the base station respectively generate corresponding digital response frames, which are used for transmitting channel parameters (that is, the arrival angle and the arrival time), and therefore may be referred to as channel parameter sending signals. The digital response frame may be broadcast to other vehicle terminals and base stations in the vicinity.
In an optional implementation manner of this embodiment, the step S105 of obtaining time offsets and positions of a plurality of vehicle terminals based on the arrival angles and arrival times of the vehicle terminals further includes the steps of:
generating a channel parameter vector based on the arrival time and the arrival angle of the vehicle terminal; the channel parameter vector comprises an arrival angle from each vehicle terminal to the base station, arrival time between every two vehicle terminals, channel gain between every two vehicle terminals, arrival time from the vehicle terminals to the base station and channel gain from the vehicle terminals to the base station;
and acquiring the clock offset and the position of each vehicle terminal according to the channel parameter vector.
In this optional implementation manner, the vehicle terminal or the base station receives a channel parameter receiving signal from another vehicle terminal or the base station, where the channel parameter receiving signal is a signal obtained after a channel parameter transmitting signal transmitted by the vehicle terminal or the base station is locally received, and the channel parameter vector may include an arrival angle from each vehicle terminal to the base station, an arrival time between every two vehicle terminals, a channel gain between every two vehicle terminals, an arrival time from the vehicle terminal to the base station, and a channel gain from the vehicle terminal to the base station, and is expressed as follows:
Figure BDA0002782838560000111
Figure BDA0002782838560000112
Figure BDA0002782838560000113
Figure BDA0002782838560000114
Figure BDA0002782838560000115
wherein the content of the first and second substances,
Figure BDA0002782838560000116
indicating the angle of arrival of each vehicle signal at the base station,/jRepresenting the arrival time vector, alpha, of the signal from the other node to the jth nodejRepresenting signals from j +1 to NaThe channel gain vector from each node to the jth node, i.e. alpha represents the channel gain between two vehicle terminals, l0Representing the arrival time vector, alpha, of the signal from the vehicle to the base station0Representing the channel gain vector of the signal arriving at the base station from the vehicle.
This is for j ≠ i and i ∈ na. Considering the position and clock offset, a channel parameter vector θ can be defined as:
Figure BDA0002782838560000121
Figure BDA0002782838560000122
wherein the content of the first and second substances,
Figure BDA0002782838560000123
indicating the clock offset of the ith node,
Figure BDA0002782838560000124
indicating the location of the ith node. It should be noted that, based on the transformation of the parameter, it can be proved that the channel parameter vector ξ can be represented by an element in the parameter vector θ. The channel parameters in the channel parameter vector θ can be estimated from the received signal: the agent (any one of the end vehicles) can receive the signal r from the receiving stationi(t) estimating the element { alpha }ij,τij:i≠j∈naThen, the base station can obtain the estimated elements, namely the arrival time and the arrival angle, from the digital response frame sent by the agent; the base station can also estimate the channel parameters of the signals from other nodes to the base station from the received signals
Figure BDA0002782838560000125
In an optional implementation manner of this embodiment, the step of obtaining the clock offset and the position of each vehicle terminal according to the channel parameter vector further includes the following steps:
determining the distance between the base station and the vehicle terminal according to the arrival time from the base station to the vehicle terminal and the arrival time from the vehicle terminal to the base station;
determining a time offset of the vehicle terminal based on a distance of the base station from the vehicle terminal, an arrival time of the base station to the vehicle terminal, and the time offset of the base station;
determining a location of the vehicle terminal based on the time offset of the vehicle terminal, the arrival time and the arrival angle of the base station to the vehicle terminal.
In this alternative implementation, once the parameter vector θ is estimated from the received signal, the parameter vector ξ may be obtained by parameter transformation, which is specifically as follows:
assuming that the elements in the channel parameter vector θ are known, the parameter vector ξ can be derived as follows:
Figure BDA0002782838560000126
Figure BDA0002782838560000131
Figure BDA0002782838560000132
Figure BDA0002782838560000133
Figure BDA0002782838560000134
Figure BDA0002782838560000135
wherein d is0iDenotes the distance, τ, from the base station to the ith vehicle terminali0And τ0iRespectively representing the arrival time from the ith vehicle terminal to the base station and the arrival time from the base station to the ith vehicle terminal; zetaiIndicates the channel gain, phi, of the ith vehicle terminal0iDenotes the angle of arrival, p, of the ith vehicle terminal to the base stationiIndicating the location of the ith vehicle terminal.
In an optional implementation manner of this embodiment, the step S105 of obtaining time offsets and positions of a plurality of vehicle terminals based on the arrival angles and arrival times of the vehicle terminals further includes the steps of:
based on the arrival angle and arrival time of the vehicle terminal, constructing a convex optimization model of the distance from the vehicle terminal to the base station and the time offset of the vehicle terminal by using a semi-positive planning method, solving the convex optimization model to obtain a preliminary solution of the time offset of the vehicle terminal, and obtaining a preliminary solution of the position of the vehicle terminal based on the preliminary solution of the time offset;
and constructing a non-convex optimization model of the Fisher-Tropsch information matrix about the time offset preliminary solution and the position preliminary solution, and solving the non-convex optimization model to obtain a target solution of the time offset and the position.
In the optional implementation manner, the channel parameter vector theta can be converted into the channel parameter vector xi by using a semi-positive definite programming method, a convex optimization model about the time offset of the vehicle terminal is constructed, a clock offset preliminary solution of the vehicle terminal can be obtained by solving the convex optimization model, and then a position preliminary solution of the vehicle terminal can be obtained by solving according to a conversion formula between the time offset and the position.
And then, establishing a Fisher information matrix taking the clock offset preliminary solution and the position preliminary solution as independent variables, establishing a non-convex optimization model by taking the inverse of the Fisher information matrix as a covariance matrix, and solving the non-convex optimization model to obtain an accurate solution of the clock offset and the position, namely a target solution. The semi-positive definite programming method and the weighting matrix method belong to the prior art, and are not described herein again.
The method solves the problems of large network synchronization error, low positioning precision and low positioning efficiency of the automatic driving vehicle. The safety and reliability of the networked automatic driving vehicle are greatly improved. Especially under the condition that GPS global positioning satellite signals are shielded, the system can replace a GPS system to protect driving of the automatic driving vehicle.
The technical details in the embodiments of the present disclosure are further illustrated by specific application examples.
Fig. 3 is a flowchart illustrating a channel parameter estimation method for estimating a channel parameter based on a ranging signal and a method for solving a clock offset and a position by a vehicle terminal and a base station according to an embodiment of the present disclosure. As shown in fig. 3, the method includes the following steps (the following takes a base station as an example, and the vehicle terminal may also apply the same channel estimation method to obtain the local arrival time and angle of arrival of other vehicles):
step 1: generating a received signal matrix; the signal matrix is represented as follows:
Figure BDA0002782838560000141
wherein R is(j)A signal matrix r representing the time domain signal received by the base station from the jth terminali (j)Discrete time for base station ith antenna receptionA domain signal corresponding to the signature signal transmitted from the terminal.
Step 2: the time of arrival and the angle of arrival are initially estimated from an objective function, wherein the objective function is expressed as follows:
Figure BDA0002782838560000142
Figure BDA0002782838560000143
Figure BDA0002782838560000144
wherein the content of the first and second substances,
Figure BDA0002782838560000145
representing a preliminary estimate of the angle of arrival of the jth node to the base station,
Figure BDA0002782838560000146
representing a preliminary estimate of the time of arrival of the jth node to the base station,
Figure BDA00027828385600001416
is a steering vector with respect to angle of arrival, b (τ) is an estimation vector with respect to time of arrival, respectively, for estimating angle of arrival and time of arrival, fcIs the carrier frequency, M is the number of antennas, M0Number of total samples of signal, TsIs the sampling period.
And step 3: entering an iterative process by continuously adjusting
Figure BDA0002782838560000147
And
Figure BDA0002782838560000148
eventually causing the objective function to converge, or alternatively,
Figure BDA0002782838560000149
or
Figure BDA00027828385600001410
The adjustment amount, i.e. the adjustment step size, is required to reach the angle threshold or the time threshold, then the preliminary estimation of the arrival time and the arrival angle is completed.
And 4, step 4: based on the preliminary estimate obtained in the previous step, i.e. the angle of arrival
Figure BDA00027828385600001411
And time of arrival
Figure BDA00027828385600001412
A convex optimization model is established by using a semi-positive definite programming method, and the distance from the base station to the vehicle terminal can be obtained by solving the convex optimization model by using CVX (composite chemical vapor deposition)
Figure BDA00027828385600001413
And clock skew
Figure BDA00027828385600001414
Then according to
Figure BDA00027828385600001415
A unique location of the vehicle terminal can be determined.
In this step, an arrival angle is established by using SDP (semi-positive definite programming method)
Figure BDA0002782838560000151
And time of arrival
Figure BDA0002782838560000152
For input data, with distance d from node i to the base station0iAnd node i clock offset ζiA model is optimized for the convex of the data to be estimated. In this model, an error matrix may be introduced. The error matrix is composed of a plurality of error relationships with respect to time, each error relationship corresponding to a node, and the error matrix is composed of a plurality of error relationships with respect to time, and the error relationships are associated with nodesRelating two times of arrival (tau) of the same link (i.e. a link between two nodes) from the node to other nodes and the base stationijAnd τji) Clock offset ζ of the nodeiAnd the actual distance between the node and other nodes and the base station, and the purpose of introducing an error matrix is to convert zeta intoiAnd d0iIntroduced into the model. In the optimization process of the convex optimization model, an objective function consists of a product of an error matrix and a semi-positive definite matrix, and the clock offset and the distance corresponding to the minimum value of the objective function are the distances estimated by the convex optimization model
Figure BDA0002782838560000153
And clock skew
Figure BDA0002782838560000154
. Then according to
Figure BDA0002782838560000155
A unique location of the vehicle terminal can be determined.
And 5: vehicle position obtained based on previous step
Figure BDA0002782838560000156
And clock skew
Figure BDA0002782838560000157
Obtaining an initial estimation matrix
Figure BDA0002782838560000158
(as defined above with respect to ξ), and then a Fisher information matrix (EFIM) (the argument of EFIM is the estimation matrix)
Figure BDA0002782838560000159
) As a covariance matrix, the EFIM matrix is introduced with the aim that it contains more information about the clock offset and the position of the vehicle terminals (say signal-to-noise ratio ωijBandwidth of baseband signal) of the algorithm by introducing such information, the measurement accuracy of the algorithm can be improved. Using the covariance matrix to construct an estimate matrix
Figure BDA00027828385600001510
The objective function of the non-convex optimization model can be composed of EFIM and parameter vectors
Figure BDA00027828385600001511
The estimation matrix corresponding to the minimum value of the objective function is the high-precision solution obtained in the step
Figure BDA00027828385600001512
. The high-precision solution can be obtained by solving through a Newton method.
Fig. 4 shows a schematic frame structure of a positioning system of a vehicle terminal in 5G internet automatic driving according to an embodiment of the present disclosure. As shown in fig. 4, the system includes a plurality of vehicle terminals 401 and a base station 402. The vehicle terminal 401 transmits a signature signal to the other vehicle terminal 401 and the base station 402;
vehicle terminal 401 also receives a ranging signal from the other vehicle terminal, the ranging signal corresponding to the signature signal sent by the other vehicle terminal;
the vehicle terminal 401 estimates a first arrival angle and a first arrival time from the other vehicle terminal to the vehicle terminal 401 according to the ranging signal, generates a channel parameter sending signal based on the first arrival angle and the first arrival time, and sends the channel parameter sending signal to the other vehicle terminal and the base station 402;
the base station 402 receives ranging signals from the plurality of vehicle terminals 401, and estimates a second angle of arrival and a second time of arrival of the vehicle terminals 401 to the base station 402 based on the ranging signals;
the base station 402 generates a channel parameter transmission signal based on the second angle of arrival and the second time of arrival, and transmits the channel parameter transmission signal to the vehicle terminal 401;
the base station 402 receives a channel parameter transmission signal from the vehicle terminal 401, the channel parameter transmission signal corresponding to the channel parameter transmission signal, and the base station 402 calculates a time offset from the vehicle terminal 401 to the base station 402 and a position of the vehicle terminal 401 based on the channel parameter transmission signals received from the plurality of vehicle terminals 401.
The processes of estimating the channel parameters and solving the clock offset and the position according to the channel parameters by the vehicle terminal 401 and the base station 402 may refer to the description of the method, and are not described herein again.
Fig. 5 shows a schematic system framework of a vehicle terminal or a base station according to an embodiment of the present disclosure. As shown in fig. 5, the system frame includes three parts:
and the data transmission part is used for transmitting signals, and the used transmission technology comprises full duplex, point-to-point, antenna array and the like.
And the frame classification part is used for classifying the transmitted data frames into two types, one type is a measurement frame for bearing the signature signal, and the other type is a digital response frame for bearing the channel parameter information.
And the vehicle terminal and the base station transmit the two types of data frames by adopting full duplex, point-to-point and antenna arrays of a data transmission part.
The vehicle terminal and the base station can estimate channel estimation parameters such as arrival time and arrival angle by applying a channel estimation algorithm through the content in the received measurement frame, and then combine the channel estimation parameters into a digital response frame.
And after the digital response frame is received by the vehicle terminal and the base station, taking the content of the digital response frame as the input of a semi-positive planning method, and further calculating to obtain a preliminary solution of the clock offset and the position of the vehicle terminal.
And taking the preliminary solution of the clock offset and the position as the input of a weighting estimation algorithm, and solving an accurate solution of the clock offset and the position by using a weighting matrix.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
According to the positioning device of the vehicle terminal in the 5G networking automatic driving of the embodiment of the disclosure, the device can be realized to be part or all of electronic equipment through software, hardware or a combination of the software and the hardware. The device comprises:
the first receiving module is configured to receive ranging signals from a plurality of vehicle terminals by using an antenna array on a base station respectively, and generate a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
a construction module configured to construct an objective function using the signal matrix, the objective function being used to estimate arrival times and arrival angles of the ranging signals from the vehicle terminals to the base station, and the objective function being used to solve for the arrival time when a steering vector of the arrival angles and an estimated vector of the arrival times are maximum;
a solving module configured to solve the arrival angle and the arrival time when a product of a steering vector formed by the arrival angle of each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using the objective function in an iterative manner;
a second receiving module configured to receive a channel parameter transmission signal from the vehicle terminal using the antenna array; the channel parameter transmission signal comprises arrival angles and arrival times corresponding to other vehicle terminals estimated by the vehicle terminals;
an obtaining module configured to obtain time offsets and positions of a plurality of the vehicle terminals based on the arrival angles and arrival times of the vehicle terminals.
In an optional implementation of this embodiment, the ranging signal includes a signature signal transmitted by the vehicle terminal, the signature signal being generated by the vehicle terminal by a pseudorandom code sequence.
In an optional implementation manner of this embodiment, after solving the norm, the apparatus further includes:
a generating module configured to generate a channel parameter transmission signal comprising the angle of arrival and the time of arrival;
a broadcasting module configured to broadcast the channel parameter transmission signal.
In an optional implementation manner of this embodiment, the obtaining module includes:
a generation submodule configured to generate a channel parameter vector based on an arrival time and an arrival angle of the vehicle terminal; the channel parameter vector comprises an arrival angle from each vehicle terminal to the base station, arrival time between every two vehicle terminals, channel gain between every two vehicle terminals, arrival time from the vehicle terminals to the base station and channel gain from the vehicle terminals to the base station;
and the first acquisition submodule is configured to acquire the clock offset and the position of each vehicle terminal according to the channel parameter vector.
In an optional implementation manner of this embodiment, the obtaining sub-module includes:
a first determination submodule configured to determine a distance of the base station from the vehicle terminal according to the arrival time of the base station from the vehicle terminal and the arrival time of the vehicle terminal from the base station to the base station;
a second determination submodule configured to determine a time offset of the vehicle terminal based on a distance of the base station from the vehicle terminal, an arrival time of the base station to the vehicle terminal, and the time offset of the base station;
a third determination submodule configured to determine a location of the vehicular terminal based on the time offset of the vehicular terminal, the arrival time and the arrival angle of the base station to the vehicular terminal.
The acquisition module includes:
a second obtaining sub-module configured to obtain a preliminary solution of a time offset and a position of the vehicle terminal by using a semi-positive planning method based on the arrival angle and arrival time of the vehicle terminal;
and the third acquisition sub-module is configured to acquire a target solution of the time offset and the position by using a weighting matrix method based on the preliminary solution.
The method for positioning the vehicle terminal in the 5G networking automatic driving in this embodiment corresponds to and is consistent with the positioning device of the vehicle terminal in the 5G networking automatic driving, and specific details can be referred to the description of the method for positioning the vehicle terminal in the 5G networking automatic driving, and are not described herein again.
Fig. 6 is a schematic structural diagram of an electronic device suitable for implementing a method for positioning a vehicle terminal in 5G internet autonomous driving according to an embodiment of the present disclosure.
As shown in FIG. 6, electronic device 600 includes a processing unit 601 that may be implemented as a CPU, GPU, FPAG, NPU, or other processing unit. The processing unit 601 may perform various processes in the embodiments of any one of the above-described methods of the present disclosure according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to embodiments of the present disclosure, any of the methods described above with reference to embodiments of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing any of the methods of the embodiments of the present disclosure. In such embodiments, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims (9)

1. A method for positioning a vehicle terminal in 5G networking automatic driving comprises the following steps:
receiving ranging signals transmitted by a vehicle terminal in a full duplex radio mode from a plurality of vehicle terminals by utilizing an antenna array on a base station, and generating a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
constructing an objective function using the signal matrix, the objective function being used to estimate arrival times and arrival angles of the ranging signals from the vehicle terminals to the base station, and the objective function being used to solve for the arrival time when the product of a steering vector of the arrival angles and an estimated vector of the arrival times is maximum;
solving the arrival angle and the arrival time when the product of a steering vector formed by the arrival angle from each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using the objective function in a continuous iteration mode;
receiving a channel parameter transmission signal from the vehicle terminal using the antenna array; the channel parameter transmission signal comprises arrival angles and arrival times of other vehicle terminals to the vehicle terminal estimated by the vehicle terminals;
and obtaining the time offset and the position of each vehicle terminal in the plurality of vehicle terminals relative to a base station based on the arrival angle and the arrival time obtained by solving the objective function and the arrival angle and the arrival time in the channel parameter transmission signal.
2. The method of claim 1, wherein the ranging signal comprises a signature signal transmitted by the vehicle terminal, the signature signal generated by the vehicle terminal through a pseudorandom code sequence.
3. The method of claim 1 or 2, wherein, after solving for the arrival angle and the arrival time at which a product of a steering vector formed by the arrival angle of each of the vehicle terminals to the base station and an estimated vector formed by the arrival time is maximum by using the objective function in an iterative manner, the method further comprises:
generating a channel parameter transmission signal, the channel parameter transmission signal comprising the angle of arrival and the time of arrival;
broadcasting the channel parameter transmission signal.
4. The method of claim 1 or 2, wherein obtaining time offsets and positions of a plurality of the vehicle terminals based on the angle of arrival and the time of arrival solved for with the objective function and the angle of arrival and the time of arrival in the channel parameter transmission signals comprises:
generating a channel parameter vector based on the arrival angle and the arrival time obtained by solving with the objective function, and the arrival angle and the arrival time in the channel parameter transmission signal; the channel parameter vector comprises an arrival angle from each vehicle terminal to the base station, arrival time between every two vehicle terminals, channel gain between every two vehicle terminals, arrival time from the vehicle terminals to the base station and channel gain from the vehicle terminals to the base station;
determining the distance between the base station and the vehicle terminal according to the arrival time from the base station to the vehicle terminal and the arrival time from the vehicle terminal to the base station;
determining a time offset of the vehicle terminal based on a distance of the base station from the vehicle terminal, an arrival time of the base station to the vehicle terminal, and the time offset of the base station;
determining a location of the vehicle terminal based on the time offset of the vehicle terminal, the arrival time and the arrival angle of the base station to the vehicle terminal.
5. The method of claim 1, wherein obtaining time offsets and locations for a plurality of the vehicle terminals based on the angle of arrival and the time of arrival solved for with the objective function and the angle of arrival and the time of arrival in the channel parameter transmission signals comprises:
on the basis of the arrival angle and the arrival time obtained by solving through the objective function and the arrival angle and the arrival time in the channel parameter transmission signal, a convex optimization model of the distance from the vehicle terminal to the base station and the time offset of the vehicle terminal is built through a semi-positive planning method, the convex optimization model is solved to obtain a preliminary solution of the time offset of the vehicle terminal, and a preliminary solution of the position of the vehicle terminal is obtained on the basis of the preliminary solution of the time offset;
and constructing a non-convex optimization model of the Fisher-Tropsch information matrix about the time offset preliminary solution and the position preliminary solution, and solving the non-convex optimization model to obtain a target solution of the time offset and the position.
6. A positioning system for a vehicle terminal in 5G networking automatic driving comprises: a plurality of vehicle terminals and base stations;
the vehicle terminal sends signature signals to other vehicle terminals and the base station in a full-duplex radio mode;
the vehicle terminal also receives a ranging signal from the other vehicle terminal by means of full duplex radio, wherein the ranging signal corresponds to the signature signal sent by the other vehicle terminal;
the vehicle terminal estimates a first arrival angle and a first arrival time from the other vehicle terminal to the vehicle terminal according to the ranging signal, generates a channel parameter sending signal based on the first arrival angle and the first arrival time, and sends the channel parameter sending signal to the other vehicle terminal and the base station;
the base station receives ranging signals from a plurality of the vehicle terminals, and estimates a second arrival angle and a second arrival time of the vehicle terminals to the base station based on the ranging signals;
the estimating a second angle of arrival and a second time of arrival of the vehicle terminal to the base station based on the ranging signal comprises:
generating a signal matrix including ranging signals received from each vehicle terminal according to the ranging signals, constructing an objective function by using the signal matrix, wherein the objective function is used for estimating arrival time and arrival angle of the ranging signals from the vehicle terminals to the base station, solving the arrival time when the product of a steering vector of the arrival angle and an estimation vector of the arrival time is maximum, and solving the second arrival angle and the second arrival time when the product of a steering vector formed by the arrival angle of the vehicle terminals to the base station and the estimation vector formed by the arrival time is maximum by using the objective function in a continuous iteration mode;
the base station generates a channel parameter sending signal based on the second arrival angle and the second arrival time, and sends the channel parameter sending signal to the vehicle terminal;
the base station receives a channel parameter transmission signal from the vehicle terminal, the channel parameter transmission signal corresponding to the channel parameter transmission signal, the base station calculates a time offset of the vehicle terminal to the base station and a position of the vehicle terminal based on the channel parameter transmission signals, the second angle of arrival and the second time of arrival received from a plurality of the vehicle terminals.
7. A positioning device for a vehicle terminal in 5G networking automatic driving comprises:
the first receiving module is configured to receive ranging signals transmitted by the vehicle terminals in a full duplex radio mode from the plurality of vehicle terminals by utilizing the antenna array on the base station, and generate a signal matrix comprising the ranging signals received from each vehicle terminal according to the ranging signals; wherein each ranging signal comprises a plurality of time domain signals received by a plurality of antennas in the antenna array;
a construction module configured to construct an objective function using the signal matrix, the objective function being used to estimate arrival times and arrival angles of the ranging signals from the vehicle terminals to the base station, and the objective function being used to solve for the arrival time when a product of a steering vector of the arrival angle and an estimated vector of the arrival time is maximum;
a solving module configured to solve the arrival angle and the arrival time when a product of a steering vector formed by the arrival angle of each vehicle terminal to the base station and an estimation vector formed by the arrival time is maximum by using the objective function in an iterative manner;
a second receiving module configured to receive a channel parameter transmission signal from the vehicle terminal using the antenna array; the channel parameter transmission signal comprises arrival angles and arrival times of other vehicle terminals to the vehicle terminal estimated by the vehicle terminals;
an obtaining module configured to obtain a time offset and a position of each of the plurality of vehicle terminals with respect to a base station based on the angle of arrival and the time of arrival solved by the objective function and the angle of arrival and the time of arrival in the channel parameter transmission signal.
8. An electronic device, comprising a memory and a processor; wherein the content of the first and second substances,
the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the processor to implement the method of any one of claims 1-5.
9. A computer readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method of any of claims 1-5.
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