WO2020177042A1 - 确定位置的方法及设备 - Google Patents

确定位置的方法及设备 Download PDF

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Publication number
WO2020177042A1
WO2020177042A1 PCT/CN2019/076775 CN2019076775W WO2020177042A1 WO 2020177042 A1 WO2020177042 A1 WO 2020177042A1 CN 2019076775 W CN2019076775 W CN 2019076775W WO 2020177042 A1 WO2020177042 A1 WO 2020177042A1
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WIPO (PCT)
Prior art keywords
terminal device
parameter
pseudorange
terminal
likelihood function
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PCT/CN2019/076775
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English (en)
French (fr)
Inventor
卢前溪
沈渊
刘袁鹏
Original Assignee
Oppo广东移动通信有限公司
清华大学
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Application filed by Oppo广东移动通信有限公司, 清华大学 filed Critical Oppo广东移动通信有限公司
Priority to PCT/CN2019/076775 priority Critical patent/WO2020177042A1/zh
Priority to CN201980081690.9A priority patent/CN113170408B/zh
Publication of WO2020177042A1 publication Critical patent/WO2020177042A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/40—Correcting position, velocity or attitude
    • G01S19/41—Differential correction, e.g. DGPS [differential GPS]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
    • 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

Definitions

  • the embodiments of the present application relate to the field of communications, and more specifically, to a method and device for determining a position.
  • the embodiments of the present application provide a method and device for determining a position, which can realize precise positioning of a terminal device.
  • a method for determining a position including: determining a position of a first terminal device according to a first parameter, the first parameter including at least two of the following parameters: the first terminal device and The pseudorange between the satellites, the pseudorange between the first terminal device and the network device, the angle between the first terminal device and the network device, the difference between the first terminal device and the second terminal device Or the first parameter includes the pseudorange between the first terminal device and the second terminal device.
  • a communication device in a second aspect, can execute the foregoing first aspect or the method in any optional implementation of the first aspect.
  • the communication device may include a functional module for executing the foregoing first aspect or any possible implementation manner of the first aspect.
  • a communication device including a processor and a memory.
  • the memory is used to store a computer program
  • the processor is used to call and run the computer program stored in the memory to execute the above-mentioned first aspect or the method in any possible implementation of the first aspect.
  • a chip for implementing the foregoing first aspect or any possible implementation of the first aspect.
  • the chip includes a processor, configured to call and run a computer program from the memory, so that the device installed with the chip executes the method in the first aspect or any possible implementation of the first aspect.
  • a computer-readable storage medium for storing a computer program that enables a computer to execute the method in the first aspect or any possible implementation of the first aspect.
  • a computer program product including computer program instructions that cause a computer to execute the foregoing first aspect or the method in any possible implementation manner of the first aspect.
  • a computer program which when running on a computer, causes the computer to execute the above-mentioned first aspect or the method in any possible implementation of the first aspect.
  • a communication system including a communication device, wherein the communication device is configured to: determine the location of a first terminal device according to a first parameter, the first parameter including at least two of the following parameters : The pseudorange between the first terminal device and the satellite, the pseudorange between the first terminal device and the base station, the angle between the first terminal device and the base station, the first terminal device and the first terminal device A pseudorange between two terminal devices, or the first parameter includes a pseudorange between the first terminal device and the second terminal device.
  • the technical solution provided by the present application can combine multiple measurement parameters to determine the position of the terminal device. Compared with a solution that only uses a single measurement quantity for positioning, the positioning accuracy can be improved.
  • the embodiment of the present application also provides a positioning solution based on the pseudorange between terminal devices, which can realize the positioning of terminal devices without the assistance of base stations or satellites.
  • Fig. 1 is a schematic diagram of a vehicle networking communication mode provided by an embodiment of the present application.
  • Fig. 2 is a schematic diagram of another vehicle networking communication mode provided by an embodiment of the present application.
  • FIG. 3 is a schematic structural diagram of an antenna array for angle measurement according to an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of a method for determining a position provided by an embodiment of the present application.
  • Fig. 5 is a schematic block diagram of a communication device according to an embodiment of the present application.
  • Fig. 6 is a schematic structural diagram of another communication device according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a chip of an embodiment of the present application.
  • Fig. 8 is a schematic block diagram of a communication system according to an embodiment of the present application.
  • GSM Global System of Mobile Communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • GSM Global System of Mobile Communication
  • GPRS General Packet Radio Service
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • the network device mentioned in the embodiment of the present application may be a device that communicates with a terminal device (or called a communication terminal or terminal).
  • the network device can provide communication coverage for a specific geographic area, and can communicate with terminal devices located in the coverage area.
  • the network device 110 may be a base station (Base Transceiver Station, BTS) in a GSM system or a CDMA system, a base station (NodeB, NB) in a WCDMA system, or an evolved base station in an LTE system (Evolutional Node B, eNB or eNodeB), or a base station (gNB) in a new wireless system, or a wireless controller in a cloud radio access network (Cloud Radio Access Network, CRAN), or the network device can be a mobile Switching centers, relay stations, access points, in-vehicle devices, wearable devices, hubs, switches, bridges, routers, network-side devices in 5G networks, or future evolution of public land mobile networks (Public Land Mobile Network, PLMN) Network
  • the terminal device mentioned in the embodiment of the present application may be any terminal device that needs to determine location information.
  • the terminal equipment can refer to an access terminal, user equipment (UE), user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile equipment, user terminal, terminal, wireless communication equipment, user agent Or user device.
  • the access terminal can be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a wireless local loop (Wireless Local Loop, WLL) station, a personal digital processing (Personal Digital Assistant, PDA), with wireless communication Functional handheld devices, computing devices or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, terminal devices in 5G networks, or terminal devices in the future evolution of PLMN, etc.
  • SIP Session Initiation Protocol
  • WLL Wireless Local Loop
  • PDA Personal Digital Assistant
  • the terminal device may be a vehicle-mounted terminal in the Internet of Vehicles, which requires very high vehicle position accuracy. Vehicles need to accurately determine their current location in order to better realize unmanned driving.
  • Terminal equipment needs to be positioned in various scenarios to better realize the functions of the terminal equipment. For example, in the navigation system of a terminal device, the terminal device needs to accurately locate the current location in order to plan a reasonable navigation route for the user and improve the user experience.
  • the embodiments of the present application can be applied to any terminal device-to-terminal device communication framework.
  • V2V vehicle-to-vehicle
  • V2X vehicle-to-everything
  • D2D device-to-device
  • the embodiments of the present application may be applicable to transmission mode 3 and transmission mode 4 defined in the third generation partnership project (3rd generation partnership project, 3GPP) Rel-14.
  • 3rd generation partnership project 3rd generation partnership project, 3GPP
  • Fig. 1 is a schematic diagram of Mode 3 of an embodiment of the present application.
  • Fig. 2 is a schematic diagram of Mode 4 of an embodiment of the present application.
  • the transmission resources of the vehicle-mounted terminal are allocated by the base station 110, and the vehicle-mounted terminal transmits data on the side link according to the resources allocated by the base station 110 .
  • the base station 110 may allocate resources for a single transmission to the terminal, or allocate resources for semi-static transmission to the terminal.
  • the vehicle terminal adopts a sensing and reservation transmission mode, and the vehicle terminal independently selects the resources of the side link Transmission resources for data transmission.
  • the vehicle needs to determine the current position in real time to avoid collisions with other objects.
  • the commonly used positioning method is to use base stations for positioning, or to use satellites for positioning.
  • Base station positioning may be based on observed time difference of arrival (OTDOA) positioning. Satellite positioning can be based on a hyperbolic positioning algorithm. The principles of these two positioning methods are the same. The following uses satellites as an example to illustrate their algorithms.
  • the satellite can send a signal to the terminal equipment, and the terminal equipment can determine the signal arrival time difference according to the reception time of the signal and the time when the satellite transmits the signal; according to the signal arrival time difference, determine the measurement between the terminal equipment and the satellite distance.
  • the terminal equipment determines the signal arrival time difference, because the terminal equipment clock is not synchronized with the satellite clock, there is a clock deviation, or in the signal transmission process, due to the influence of signal noise, clock noise and other factors, the terminal equipment determines the signal arrival
  • the time difference is not equal to the real signal transmission time, so the distance calculated from the arrival time difference is not the real distance between the terminal device and the satellite. We can call this measured distance a pseudorange.
  • the position of the terminal device can be determined according to the pseudorange between the terminal device and the satellite.
  • a certain satellite can be used as a reference satellite, and the pseudoranges of other satellites can be subtracted from the pseudoranges of the reference satellites to obtain the difference between the pseudoranges of the two satellites. Since the difference can eliminate the influence of the clock deviation of the terminal device, the difference in the pseudorange can more realistically approximate the distance difference between the two satellites and the terminal device.
  • the position estimation of the vehicle can be obtained by using the Taylor algorithm of the first-order approximation by performing the least square cost function on the multiple distance differences.
  • terminal equipment has higher and higher requirements for positioning accuracy.
  • the requirements for positioning accuracy are more stringent.
  • the above-mentioned least squares cost function is not accurate enough, and the first-order approximation Taylor algorithm is directly used for positioning, which will lead to easy convergence to the wrong position when the measurement error is large, so that the calculated position of the terminal device is between the actual position The error is large and the positioning accuracy is not high.
  • the satellite system can only achieve meter-level two-dimensional plane accuracy due to its special high-altitude characteristics, while the altitude positioning accuracy is very poor, reaching ten meters.
  • the positioning accuracy of the base station is higher than that of the satellite, the base station is easily blocked, resulting in a limited number of vehicles that can be obtained by the vehicle, and the vehicle cannot use the blocked base station for positioning; and the base station has co-channel interference, and the signal from the remote base station is easy Being interfered by nearby base station signals, the positioning accuracy of the base station is also limited, roughly at the ten-meter level.
  • Traditional positioning algorithms only rely on a single satellite system or base station system, and only consider a single measurement, such as the pseudorange of the base station or the pseudorange of the satellite. Due to the small amount of measurement, the different advantages of satellites and base stations cannot be used, and the sub-meter accuracy requirements of the Internet of Vehicles cannot be met.
  • an embodiment of the present application provides a method for determining a position, which can improve the positioning accuracy of a terminal device.
  • the method for determining a position includes step S210.
  • S210 Determine the position of the first terminal device according to the first parameter, where the first parameter includes at least two of the following parameters: the pseudorange between the first terminal device and the satellite, and the first terminal device The pseudorange with the network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and the second terminal device, or the first parameter including the first The pseudorange between a terminal device and a second terminal device.
  • the first parameter includes at least two of the following parameters: the pseudorange between the first terminal device and the satellite, and the first terminal device The pseudorange with the network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and the second terminal device, or the first parameter including the first The pseudorange between a terminal device and a second terminal device.
  • the first terminal device may be a vehicle-mounted terminal in the Internet of Vehicles system, such as a vehicle; it may also be a terminal device of other networks, such as a mobile terminal, etc.
  • the embodiment of the application does not specifically limit the type of the first terminal device.
  • the second terminal device in the embodiment of the present application may refer to any terminal device other than the first terminal device.
  • the network device in the embodiment of the present application may be a base station, for example.
  • the following description takes the network device as a base station as an example.
  • the first parameter is a parameter obtained through measurement, such as a pseudorange measurement value and an angle measurement value.
  • it can also implement angle measurement of the terminal device.
  • the first parameter may also include the angle measurement value between the terminal devices.
  • the technical solution provided by the embodiments of the present application can integrate the measurement quantities in the base station system, the satellite system and the terminal network system to perform the positioning of the terminal device. Compared with the single measurement quantity scheme, the positioning accuracy can be improved.
  • the first parameter may also include only one of the above parameters.
  • the first parameter may only include the pseudorange between the terminal equipment, or only the angle between the first terminal equipment and the base station. Through the first parameter, the location of the first terminal device can also be determined.
  • the position of the first terminal device may be an absolute position or a relative position.
  • the absolute position may refer to the latitude and longitude coordinates of the first terminal device, and the relative position may refer to the position of the first terminal device relative to other terminal devices.
  • the location information of the first terminal device may include the three-dimensional location information or the two-dimensional location information of the first terminal device, which is not limited in the embodiment of the present application.
  • the embodiments of the present application may collectively refer to terminal equipment, satellites, and base stations as nodes.
  • the pseudorange between the first terminal device and the node can be obtained by using a traditional method of measuring the pseudorange.
  • the satellites in the embodiments of the present application may be global positioning system (global positioning system, GPS) satellites, or Beidou satellites, etc., which is not limited.
  • global positioning system global positioning system, GPS
  • Beidou satellites Beidou satellites, etc., which is not limited.
  • the base station in the embodiment of the present application may be a base station in a 5G system, a base station in an LTE system, or a base station in other systems.
  • the angle between the first terminal device and the base station may refer to the angle between the base station and the first terminal device measured by the antenna array of the base station.
  • the angle between the first terminal device and the base station may include an azimuth angle and/or a pitch angle between the first terminal device and the base station.
  • the embodiment of the present application does not specifically limit the manner of determining the location of the first terminal device.
  • the first parameter includes the pseudo-range between the first terminal device and the satellite, and the pseudo-range between the first terminal device and the base station.
  • the method of determining the position may refer to calculating the position of the first terminal device according to the pseudo-range between the first terminal device and the satellite and the pseudo-range between the first terminal device and the base station, that is, In other words, the position X1 of the first terminal device can be calculated according to the pseudorange between the first terminal device and the satellite, and then the position X2 of the first terminal device can be calculated according to the pseudorange between the first terminal device and the base station, and finally According to the position X1 and the position X2, the position of the first terminal device is finally determined.
  • determining the position of the first terminal device may refer to taking the average value of the position X1 and the position X2 as the position of the first terminal device.
  • different weights may be respectively set for the position X1 and the position X2 to calculate the position of the first terminal device.
  • the embodiment of the present application does not limit the manner of calculating the position X1 of the first terminal device according to the pseudorange between the first terminal device and the satellite.
  • a traditional least squares cost function may be used to determine the position X1 of the first terminal device; or the position X1 of the first terminal device may also be determined according to a hyperbolic positioning algorithm.
  • the method of calculating the position X2 of the first terminal device may also adopt any of the above methods.
  • the way to determine the position can also be to merge the pseudorange between the first terminal device and the satellite, and the pseudorange between the first terminal device and the base station into a cost function, and perform Iteratively determine the location of the first terminal device.
  • the pseudorange between the first terminal device and the satellite is referred to as the pseudorange of the satellite
  • the pseudorange between the first terminal device and the base station is referred to as the pseudorange of the base station.
  • the pseudorange of the satellite and the pseudorange of the base station are used as examples.
  • the first parameter in the embodiment of the present application may also include other parameters, such as the angle between the first terminal device and the base station, and/or the first parameter.
  • the pseudorange between a terminal device and other terminal devices may also include other parameters, such as the angle between the first terminal device and the base station, and/or the first parameter.
  • the first parameter may also include other measurement quantities.
  • the positioning can also be performed according to the angle between the terminal devices.
  • Any parameter that can be used for position determination can be included in the first parameter.
  • weights may also be set for different parameters.
  • each parameter in the first parameter has its own weight information.
  • the weights of different parameters may be the same or different, and the specific weight information may be determined according to actual conditions.
  • the embodiment of the present application may determine the location of the first terminal device according to the first parameter and the weight information of each parameter in the first parameter.
  • different weights can be set for different parameters according to specific conditions. For example, when the measurement parameter is relatively accurate, you can set a higher weight for the parameter, and when the measurement parameter error is large, set a lower weight for the parameter, so that the first terminal is determined according to multiple parameters.
  • the location of the device can ensure the accuracy of the location of the first terminal device.
  • noise can include signal noise and/or clock noise. Since noise cannot be eliminated and is inevitable, we can minimize the impact of noise when determining the location of the terminal equipment.
  • different weights can be set for different parameters based on noise to improve positioning accuracy.
  • the pseudorange between the first terminal device and the satellite has a first weight
  • the pseudorange between the first terminal device and the base station has a second weight
  • the pseudorange between the first terminal device and the second terminal device has a third weight
  • Weight the angle between the first terminal device and the base station has a fourth weight.
  • the first weight can be determined according to the variance of the signal noise when determining the weight.
  • the second weight and the third weight may be jointly determined according to the variance of the signal noise and the variance of the clock noise.
  • the angle between the base station and the first terminal device is also affected by signal noise. Therefore, the fourth weight may be determined according to the covariance of signal noise.
  • the first weight may be the inverse of the variance of signal noise
  • the second and third weights may be the inverse of the sum of the variance of signal noise and the variance of clock noise
  • the fourth weight may be the covariance of signal noise
  • the pseudorange between the first terminal device and the second terminal device may be used to determine the estimated distance
  • the estimated distance may be the pseudorange between the first terminal device and the second terminal device
  • the first terminal device Second, the average value of the pseudorange between the terminal device and the first terminal device obtained by the terminal device; then, determining the position of a terminal device according to the first parameter may refer to determining the position of the first terminal device according to the estimated distance.
  • the embodiment of the application utilizes the feature of two-way ranging between terminal devices.
  • the average value of the two-way ranging that is, the distance estimate
  • the distance estimate can eliminate the terminal equipment
  • the distance estimate can more truly reflect the distance between two terminal devices, so that the use of the distance estimate for positioning can also improve positioning accuracy.
  • the embodiment of the present application does not limit the algorithm used to determine the location of the first terminal device.
  • a maximum likelihood function may be constructed based on the maximum likelihood theory, and the position of the first terminal device may be determined by the maximum likelihood function. The maximum likelihood function will be described in detail below.
  • the maximum likelihood function may also include a clock deviation parameter. While determining the location of the terminal device, this application can also determine the clock deviation of the terminal device. Specifically, the clock deviation of the first terminal device can be calculated according to the first parameter and the maximum likelihood function.
  • Calculating the maximum likelihood function and determining the position of the terminal device can be performed by any node among the terminal device, the base station and the satellite.
  • the likelihood function may be a centralized likelihood function, which means that the location information of all terminal devices is obtained by iterating the likelihood function by the same computing node.
  • the likelihood function may be a distributed likelihood function, which means that each terminal device only calculates its own location information.
  • the positions of the multiple terminal devices may be obtained by respectively iterating the likelihood function for each of the multiple terminal devices.
  • the first terminal device determines the location of the first terminal device according to the first parameter and the maximum likelihood function, which may mean that the first terminal device can iterate the likelihood function according to the first parameter to obtain the first terminal device’s m iteration parameter, m is an integer greater than or equal to 1; then the m iteration parameter of the other terminal device among the multiple terminal devices and the m iteration parameter of the first terminal device can be used to determine the The (m+1)th iteration parameter; repeat the above steps until all iteration parameters no longer change or the maximum number of iterations is reached; the position of the first terminal device is determined according to the last iteration parameter.
  • N c terminal devices there are N c terminal devices, N b base stations, and N s satellites in the system, where the positions of the base stations and satellites are known.
  • the N c terminal devices can calculate pseudo-ranges with N b base stations and/or pseudo-ranges with N s satellites.
  • the set of terminals, base stations and satellites is defined as follows: with
  • the terminal device may be a vehicle, and N c terminal devices may refer to N c vehicles in the car networking system.
  • node k including terminal equipment, base station, and satellite
  • p k [x k ,y k ,z k ] T
  • parameter vector containing the positions of all terminal equipment is denoted as
  • the embodiments of the present application may assume that the satellite and the base station are synchronized, that is, there is no clock deviation between the satellite and the base station. Due to the limitation of hardware equipment, terminal equipment k has a clock deviation ⁇ k from the base station and satellite.
  • p k represents the position of the node
  • p j represents the position of the node j.
  • the node k may receive the signal from the node j.
  • the node k may be, for example, the first terminal device, and the node j may be any one of a satellite, a base station, and other terminal devices.
  • Node k can receive the signal from node j, which can be written as follows:
  • s j (t) is a known signal, its Fourier transform is S j (f), ⁇ kj and ⁇ kj are the signal amplitude and time delay of the transmission link from node j to node k, respectively, n kj (t ) Is Gaussian white noise with a power spectral density of N 0 /2.
  • the signal received by node k also includes noise signal n kj (t).
  • d kj represents the actual distance between node k and node j
  • b k represents the distance deviation introduced by the clock deviation of node k
  • ⁇ kj is due to signal noise n kj (t)
  • b k c* ⁇ k
  • c is the speed of light
  • ⁇ k represents the clock deviation of node k (or terminal device k).
  • the embodiment of the present application may be used to determine the weight of the pseudorange between node k and node j based on the variance of ⁇ kj .
  • the variance can be The reciprocal of is determined as the weight of the pseudorange between node k and node j.
  • the variance is inversely proportional to the signal-to-noise ratio and the equivalent bandwidth, and the variance can be reduced by increasing the signal-to-noise ratio and the equivalent bandwidth.
  • b j represents the distance deviation caused by the clock offset of node j
  • ⁇ kj represents the distance error caused by clock noise. If clock noise is not calibrated, its variance Will grow over time. The variance of the clock noise It can be obtained in the factory parameters of the clock.
  • node j is a base station
  • the pseudorange model can be expressed as:
  • node j is a satellite
  • node j is a base station or other terminal equipment:
  • the embodiment of the application also considers the property that the base station can measure the angle.
  • the base station j can measure the elevation angle ⁇ jk and the azimuth angle ⁇ jk with the terminal device k, and the modeling can be as follows:
  • ⁇ jk represents the actual pitch angle between node j and node k
  • ⁇ jk represents the actual azimuth angle between node j and node k
  • ⁇ jk represents the signal
  • the covariance matrix of the equivalent zero-mean Gaussian noise at the two-dimensional angle introduced by the noise can be represented by C jk .
  • C jk is related to the spatial structure of the base station antenna array.
  • the spatial structure of the base station antenna array may be, for example, a rectangular array or a circular array.
  • C jk has different expressions.
  • the following description takes the antenna array of the base station as a rectangular array as an example. As shown in FIG. 4, it is assumed that the antenna array of the base station is an M ⁇ N rectangular array.
  • [Delta] is a spaced array elements in FIG, or, [Delta] may be understood as row spacing or column spacing, [lambda] is the wavelength of the signal, ⁇ jk is the covariance matrix C jk may be expressed as:
  • the location of the terminal device can be calculated through traditional algorithms.
  • the location of the terminal device may also be calculated based on the maximum likelihood function provided in the embodiment of the present application.
  • p k represents the location of node k
  • node k can be a terminal device
  • p j represents the location of node j
  • node j can be any of terminal devices, base stations, and satellites
  • ⁇ p k -p j ⁇ represents a node The actual distance between k and j.
  • the above formula represents the maximum likelihood of the pseudorange of the base station or satellite.
  • the above formula represents the maximum likelihood of pseudoranges between terminal devices.
  • the above formula represents the maximum likelihood of the angle between the base station and the terminal device.
  • multiple measurement items are considered, and multiple measurement items may be integrated into a cost function, and the cost function may be iterated multiple times until the cost function converges or When the maximum number of iterations is reached, then the last iteration parameter can be determined as the location of the terminal device.
  • the likelihood function provided by the embodiment of the application also takes into account the influence of clock deviation, and the distance deviation caused by the clock deviation is also introduced into the likelihood function for calculation.
  • the terminal can also be obtained.
  • the clock deviation can play an important role in the subsequent communication process of the terminal device.
  • the terminal device can inform the opposite terminal device of its clock deviation, which is beneficial to subsequent communication.
  • the likelihood function of the embodiment of the present application is not limited to the above-mentioned form.
  • the distance deviation caused by the clock deviation can also be ignored, and the position estimation can be performed directly through the measured pseudorange.
  • the embodiment of the present application also considers the feature that two-way ranging between terminal devices can be performed, that is, the first parameter may include the pseudorange obtained by the first terminal device and the second terminal device, and the second The pseudorange obtained by the terminal device and the first terminal device. Therefore, the two-way pseudoranges measured between the first terminal device and the second terminal device are all considered and integrated into the likelihood function to further improve the positioning accuracy.
  • the pseudorange between the first terminal device k and the second terminal device j may mean that the second terminal device j may send a first signal to the first terminal device, and the first signal may include the second terminal device j sending The transmission time t1 of the first signal. After the first terminal device k receives the first signal, it can determine the pseudorange to the second terminal device j according to its own receiving time t2 as
  • the pseudorange between the second terminal device j and the first terminal device k may refer to that the first terminal device k may send a second signal to the second terminal device j, and the second signal may include the first terminal device k The sending time t3 of sending the second signal. After the second terminal device j receives the second signal, it can determine the pseudorange to the first terminal device k according to its own receiving time t4 as
  • the maximum likelihood of the pseudorange between terminal devices in the maximum likelihood function can be transformed into:
  • the embodiments of the present application can also set different weights for different parameters.
  • For the pseudorange of the satellite we can only consider the influence of signal noise. Therefore, we can set the weight for the pseudorange of the satellite based on the signal noise, for example, The reciprocal of the noise variance ⁇ kj is set as the weight of the satellite pseudorange, Node j represents a satellite.
  • the pseudorange of the base station can be determined according to the variance of the signal noise and the variance of the clock noise.
  • the weight of the pseudorange of the base station can be the signal noise.
  • Node j represents a base station.
  • the weight can be, for example, Node j represents other terminal equipment.
  • the embodiment of the application may consider the influence of the equivalent zero-mean Gaussian noise on the two-dimensional angle induced by the signal noise, and the covariance matrix of the signal noise may be used to determine the weight of the angle measurement.
  • the inverse matrix of the covariance matrix is determined as the weight of the angle measurement.
  • the maximum likelihood function can be transformed into:
  • ⁇ kj is directly proportional to the signal-to-noise ratio, that is, the larger the signal-to-noise ratio, the greater the weight ⁇ kj . If the signal-to-noise ratio of a measurement is relatively large, it means that the noise in the signal is small, and then the measurement can be given a greater weight; if the signal-to-noise ratio of a measurement is relatively small, it means that the noise in the signal is relatively small Larger, you can assign a smaller weight to the measurement. This way of setting weights is more reasonable, and the influence of signal noise and clock noise is considered in the algorithm.
  • the position of the terminal device determined by the maximum likelihood function is also closer to the actual position, and the positioning accuracy is high.
  • the embodiment of the present application does not specifically limit the method used for its solution.
  • it can be a gradient descent method, an EM algorithm, a coordinate ascending or descending algorithm, etc.
  • the following takes the gradient descent algorithm as an example to describe the solution process of the likelihood function.
  • H(p,b) is expressed in the form of a weighted sum of squares. Among them, it contains two parts, one part is the information from the anchor point, such as the pseudorange and angle information from the base station, and the pseudorange information from the satellite. The other part is pseudorange information from other terminal devices. among them, Is the measured pseudorange value and angle value. Our goal is to minimize the deviation between the calculated pseudorange and angle values and the measured pseudorange and angle values.
  • the likelihood function is called a centralized positioning algorithm.
  • pseudorange measurement we take the pseudorange measurement between terminal devices as an example.
  • the first derivative of the pseudorange between base stations or satellites with respect to the position parameter p k of the terminal device and the clock deviation parameter b k can also be obtained by
  • the formula can be obtained by analogy, just take p j and b j in the polynomial as the known parameters of the corresponding satellite or base station.
  • the likelihood function can be iterated for the first time to obtain the minimum value of the first iteration. Further, the second iteration is performed according to the iteration parameters of the first iteration to obtain the iteration parameters of the second iteration. Loop in turn until the iteration parameters no longer change or the maximum number of iterations is reached.
  • the pseudorange and angle measurement values between the terminal device and all nodes can be input. Then the initial state of all terminal devices can be given with And iterate according to the initial state.
  • the weight of the pseudorange between terminal devices can be 0.3, 0.3, and 0.3 respectively. 0.2, 0.2.
  • the first parameter value only includes the pseudorange of the terminal device, if the above given gradient descent algorithm is used directly For positioning, if the given initial value is not good enough, it is easy to cause non-convergence or convergence to the wrong position, that is, the calculated position of the terminal device is very different from the actual position.
  • equation (5) is a linear model about the distance d kj and the deviations b k , b j , the least squares can be used directly to obtain all the estimates of the distance d kj and the distance deviation b k .
  • the embodiment of the present application also provides another simple way to obtain the distance estimate, that is, directly averaging the two-way distance measurement to obtain the distance estimate:
  • Using the distance estimation value for positioning can eliminate the influence of the clock deviation between the first terminal device and the second terminal device on the distance estimation.
  • the shape of the terminal equipment network can be obtained directly through the classic multi-dimensional calibration algorithm, or other algorithms such as positive semi-definite programming algorithms can also be used to obtain the "shape estimation" of the terminal equipment network.
  • the k rows and j columns of can be expressed as:
  • the realization of the multi-dimensional calibration algorithm can be as follows:
  • the above-mentioned centralized positioning algorithm needs to aggregate all the measurements in the network, and all these measurements need to be calculated in a central point, that is, the positions of all terminal devices and clock deviations are calculated through a central point.
  • the central point can be any node among terminal equipment, base stations and satellites. Because this algorithm directly calculates the p and b of N c vehicles, the solution space is large and the complexity is high, and it also has high requirements for the calculation ability of the center point.
  • the embodiment of the present application provides a distributed positioning algorithm that can decompose the calculation process.
  • Each terminal device k only needs to calculate its own position p k and clock deviation b k , so that all terminal devices can be obtained The position and clock offset.
  • This calculation method can reduce the computational complexity of the computing node, increase the calculation rate, and ensure the real-time requirements in the mobile network.
  • Each terminal device can iterate the likelihood function according to the derivation method described above, and each terminal device iterates its own likelihood function to find its corresponding position and clock offset.
  • the specific iteration process is as follows:
  • the first terminal device may iterate the distributed likelihood function according to the first parameter to obtain the m-th iteration parameter of the first terminal device, where m is an integer greater than or equal to 1.
  • the first terminal device can receive the mth iteration parameters of other terminal devices broadcasted by other terminal devices, and use the gradient descent algorithm to obtain the (m+1)th iteration of the node according to the mth iteration parameters of other terminal devices. parameter.
  • the first terminal device determines the location and clock offset of the first terminal device according to the parameters of the last iteration. For example, the first terminal device may determine p in the last iteration parameter as the location information of the first terminal device, and determine b in the last iteration parameter as the clock offset distance of the first terminal device.
  • the second terminal device can use the above steps to obtain the position and clock offset of the second terminal device.
  • each terminal device can get the position and clock offset of the node. In this way, the position and clock offset of the entire terminal equipment system can be obtained.
  • the gradient descent algorithm described above can be directly used for calculation. However, if the given initial value is not good enough, it is prone to not converge or converge to the wrong position.
  • the embodiment of the present application provides a calculation method that can avoid the situation of non-convergence or convergence to the wrong position.
  • the calculation method is described below.
  • Each terminal device can obtain the distance value between it and its neighbor through equation (6), and each terminal device can broadcast all the distance values it obtains to other terminal devices.
  • each terminal device can obtain all measurement information in its 1-hop network, that is, each terminal device can obtain the measurement information of other terminal devices that can communicate with it.
  • the terminal device can obtain the "shape" of each terminal device's one-hop network according to the distance measurement value (or pseudorange) of all nodes within the 1-hop range, according to the multi-dimensional calibration algorithm or the positive semi-definite programming algorithm.
  • these local structures can be merged to obtain the "shape" of the entire network.
  • the specific calculation process is as follows:
  • the input is the pseudorange between the terminal device and other terminal devices, and the output is the "shape" of the entire terminal device network.
  • Each terminal device can construct its own local 1-hop network "shape" for the 0th round of the multi-dimensional calibration algorithm described above And broadcast it to neighbors.
  • terminal device k start with any terminal device and set it as the starting network.
  • terminal device k take the definition of terminal device k as the starting network as an example.
  • Terminal device k can never be The terminal device j is selected from the terminal devices in so that with The maximum number of shared nodes owned is an integer greater than or equal to 1.
  • the embodiment of the application Compared with the 3GPP positioning algorithm that only contains pseudorange measurement parameters and only uses a single type of information (such as a base station or satellite), the embodiment of the application not only adds the angle measurement of the base station and the pseudorange measurement of mutual cooperation between terminal devices , And in the algorithm, all these measurements are integrated into one cost function, and the positioning accuracy can be improved through the cost function after fusion.
  • the maximum likelihood function provided in the embodiments of the present application is inclusive. For unknown measurement items or measurement items that have not been performed, it is sufficient to set the missing part of the measurement to 0, and the likelihood function can still be used for positioning. For example, in the case of only the angle measurement and pseudorange measurement of the base station, it is only necessary to set the polynomial related to the pseudorange of the satellite and the pseudorange polynomial between the terminal equipment to 0, and only perform the angle and pseudorange polynomials of the base station. Iterate to obtain the location information of the terminal device.
  • the maximum likelihood function provided by the embodiment of the present application can realize the positioning of the terminal device while also realizing the estimation of the clock offset of the terminal device.
  • the embodiment of the present application uses a gradient descent algorithm to solve the maximum likelihood function. Since the gradient descent algorithm is used, only the gradient needs to be calculated during the iteration process. And the gradient part has a closed-form expression, and the complexity is low. Especially for networks with high real-time requirements such as the Internet of Vehicles, low complexity can meet its real-time requirements.
  • the distributed positioning algorithm provided in the embodiments of the present application can further reduce computational complexity and improve real-time performance.
  • the method for determining the position provided by the embodiment of the application is described in detail above.
  • the device of the embodiment of the application is described in detail below with reference to Figs. 5 to 8.
  • the device embodiment and the method embodiment correspond to each other, so the parts not described in detail can be See the previous method embodiments.
  • FIG. 5 is a schematic block diagram of a communication device 500 according to an embodiment of the present application.
  • the communication device 500 shown in FIG. 5 may be the sending end device in the method embodiment.
  • the communication device may include a processing unit 510.
  • the processing unit 510 is configured to determine the position of the first terminal device according to a first parameter, where the first parameter includes at least two of the following parameters: the pseudorange between the first terminal device and the satellite, and The pseudorange between the first terminal device and the network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and the second terminal device, or the first terminal device A parameter includes the pseudorange between the first terminal device and the second terminal device.
  • each parameter in the first parameter has its own weight information
  • the processing unit 510 is configured to: according to the first parameter and the weight information of each parameter in the first parameter, Determine the location of the first terminal device.
  • the pseudorange between the first terminal device and the satellite has a first weight
  • the pseudorange between the first terminal device and the network device has a second weight
  • the first terminal The pseudorange between the device and the second terminal device has a third weight
  • the angle between the first terminal device and the network device has a fourth weight
  • the first weight is determined according to the variance of signal noise
  • the second weight and the third weight are determined according to the variance of signal noise and the variance of clock noise
  • the fourth weight is determined according to the covariance of signal noise.
  • the angle between the first terminal device and the network device includes an azimuth angle and/or a pitch angle.
  • the pseudorange between the first terminal device and the second terminal device is used to determine a distance estimation value, and the distance estimation value is obtained by the first terminal device and the second terminal device And the average value of the pseudorange between the second terminal device and the first terminal device obtained by the second terminal device; the processing unit 510 is configured to: determine the first terminal device according to the estimated distance value The location of the terminal device.
  • the processing unit 510 is configured to determine the location of the first terminal device according to the first parameter and a maximum likelihood function.
  • the communication device is configured to obtain the positions of multiple terminal devices
  • the multiple terminal devices include the first terminal device
  • the processing unit 510 is configured to: use gradient descent according to the first parameter
  • the algorithm performs multiple iterations on the maximum likelihood function to obtain the minimum value of the maximum likelihood function; and determines the positions of the multiple terminal devices according to the iteration parameter at the minimum value of the maximum likelihood function.
  • the positions of the multiple terminal devices are obtained by iterating the maximum likelihood function by the same computing node.
  • the positions of the multiple terminal devices are obtained by respectively iterating the maximum likelihood function of each terminal device of the multiple terminal devices, and the processing unit 510 is configured to: A parameter, iterating the maximum likelihood function to obtain the m-th iteration parameter of the first terminal device, where m is an integer greater than or equal to 1; The second iteration parameter and the mth iteration parameter of the first terminal device determine the (m+1)th iteration parameter of the first terminal device; repeat the above steps until all iteration parameters no longer change; The last iteration parameter determines the location of the first terminal device.
  • the maximum likelihood function further includes a clock deviation parameter of the first terminal device
  • the processing unit 510 is configured to: determine the clock deviation parameter according to the first parameter and the maximum likelihood function The clock deviation of the first terminal device.
  • the first parameter includes a pseudorange between the first terminal device and the second terminal device
  • the processing unit 510 is configured to: according to the first terminal device and the second terminal device
  • the pseudo-distance between the devices is determined by a square distance matrix; according to the square distance matrix, the position of the first terminal device is determined by a multi-dimensional calibration algorithm or a positive semi-definite programming algorithm.
  • the location of the first terminal device includes two-dimensional location information and/or three-dimensional location information of the first terminal device.
  • the communication device 500 can perform the corresponding operations performed by the communication device in the foregoing method, and for the sake of brevity, details are not described herein again.
  • the communication device 500 may be, for example, the terminal device, network device or satellite described above.
  • FIG. 6 is a schematic structural diagram of a communication device 600 provided by an embodiment of the present application.
  • the communication device 600 shown in FIG. 6 includes a processor 610, and the processor 610 can call and run a computer program from the memory to implement the method in the embodiment of the present application.
  • the communication device 600 may further include a memory 620.
  • the processor 610 may call and run a computer program from the memory 620 to implement the method in the embodiment of the present application.
  • the memory 620 may be a separate device independent of the processor 610, or may be integrated in the processor 610.
  • the communication device 600 may further include a transceiver 630, and the processor 610 may control the transceiver 630 to communicate with other devices. Specifically, it may send information or data to other devices, or receive other devices. Information or data sent by the device.
  • the transceiver 630 may include a transmitter and a receiver.
  • the transceiver 630 may further include an antenna, and the number of antennas may be one or more.
  • the communication device 600 may specifically be a terminal device of an embodiment of the present application, and the communication device 600 may implement the corresponding process implemented by the communication device in each method of the embodiment of the present application. For brevity, details are not repeated here. .
  • FIG. 7 is a schematic structural diagram of a chip of an embodiment of the present application.
  • the chip 700 shown in FIG. 7 includes a processor 710, and the processor 710 can call and run a computer program from the memory to implement the method in the embodiment of the present application.
  • the chip 700 may further include a memory 720.
  • the processor 77 may call and run a computer program from the memory 720 to implement the method in the embodiment of the present application.
  • the memory 720 may be a separate device independent of the processor 710, or may be integrated in the processor 710.
  • the chip 700 may further include an input interface 730.
  • the processor 710 may control the input interface 730 to communicate with other devices or chips, and specifically, may obtain information or data sent by other devices or chips.
  • the chip 700 may further include an output interface 740.
  • the processor 710 can control the output interface 740 to communicate with other devices or chips, and specifically, can output information or data to other devices or chips.
  • the chip can be applied to the terminal device in the embodiment of the present application, and the chip can implement the corresponding process implemented by the terminal device in the various methods of the embodiment of the present application.
  • the chip can implement the corresponding process implemented by the terminal device in the various methods of the embodiment of the present application.
  • chips mentioned in the embodiments of the present application may also be referred to as system-level chips, system-on-chips, system-on-chips, or system-on-chips.
  • the processor of the embodiment of the present application may be an integrated circuit chip with signal processing capability.
  • the steps of the foregoing method embodiments can be completed by hardware integrated logic circuits in the processor or instructions in the form of software.
  • the above-mentioned processor may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (ASIC), a ready-made programmable gate array (Field Programmable Gate Array, FPGA) or other Programming logic devices, discrete gates or transistor logic devices, discrete hardware components.
  • DSP Digital Signal Processor
  • ASIC application specific integrated circuit
  • FPGA Field Programmable Gate Array
  • the methods, steps, and logical block diagrams disclosed in the embodiments of the present application can be implemented or executed.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor.
  • the software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers.
  • the storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.
  • the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), and electrically available Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
  • the volatile memory may be a random access memory (Random Access Memory, RAM), which is used as an external cache.
  • RAM random access memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • DRAM synchronous dynamic random access memory
  • DDR SDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • Enhanced SDRAM, ESDRAM Enhanced Synchronous Dynamic Random Access Memory
  • Synchronous Link Dynamic Random Access Memory Synchronous Link Dynamic Random Access Memory
  • DR RAM Direct Rambus RAM
  • the memory in the embodiment of the present application may also be static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), Synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection Dynamic random access memory (Synch Link DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM), etc. That is to say, the memory in the embodiment of the present application is intended to include but not limited to these and any other suitable types of memory.
  • FIG. 8 is a schematic block diagram of a communication system 800 according to an embodiment of the present application. As shown in FIG. 8, the communication system 800 includes a network device 810 and a terminal device 820.
  • the network device 810 can be used to implement the corresponding functions implemented by the network device in the above method, and the composition of the network device 810 can be as shown in the communication device 500 in FIG. 5, for the sake of brevity, it will not be omitted here. Repeat.
  • the terminal device 820 can be used to implement the corresponding functions implemented by the terminal device in the foregoing method, and the composition of the terminal device 820 can be as shown in the communication device 500 in FIG. Repeat.
  • the embodiment of the present application also provides a computer-readable storage medium for storing computer programs.
  • the computer-readable storage medium may be applied to the network device in the embodiment of the present application, and the computer program causes the computer to execute the corresponding process implemented by the network device in each method of the embodiment of the present application.
  • the computer-readable storage medium can be applied to the terminal device in the embodiment of the present application, and the computer program causes the computer to execute the corresponding process implemented by the terminal device in each method of the embodiment of the present application.
  • the computer-readable storage medium can be applied to the terminal device in the embodiment of the present application, and the computer program causes the computer to execute the corresponding process implemented by the terminal device in each method of the embodiment of the present application. For brevity, here No longer.
  • the embodiments of the present application also provide a computer program product, including computer program instructions.
  • the computer program product may be applied to the network device in the embodiment of the present application, and the computer program instructions cause the computer to execute the corresponding process implemented by the network device in each method of the embodiment of the present application.
  • the computer program product can be applied to the terminal device in the embodiment of the present application, and the computer program instructions cause the computer to execute the corresponding process implemented by the terminal device in each method of the embodiment of the present application.
  • the computer program product can be applied to the terminal device in the embodiment of the present application, and the computer program instructions cause the computer to execute the corresponding process implemented by the terminal device in each method of the embodiment of the present application.
  • the embodiment of the present application also provides a computer program.
  • the computer program can be applied to the network device in the embodiment of the present application.
  • the computer program runs on the computer, the computer is caused to execute the corresponding process implemented by the network device in each method of the embodiment of the present application.
  • I won’t repeat it here the computer program can be applied to the terminal device in the embodiment of the present application.
  • the computer program runs on the computer, it causes the computer to execute the corresponding process implemented by the terminal device in each method of the embodiment of the present application.
  • B corresponding (corresponding) to A means that B is associated with A, and B can be determined according to A.
  • determining B according to A does not mean that B is determined only according to A, and B can also be determined according to A and/or other information.
  • the disclosed system, device, and method may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the unit is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of this application essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .

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Abstract

本申请公开了一种确定位置的方法及设备，该方法包括：根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与所述网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。该方法可以结合多个测量参数，来确定终端设备的位置，相比于仅采用单一的测量量进行定位的方案，能够提高定位精度。

Description

确定位置的方法及设备 技术领域
本申请实施例涉及通信领域，并且更具体地，涉及确定位置的方法及设备。
背景技术
随着技术的发展，越来越多的终端设备需要进行定位，且用户对终端设备的定位精度要求越来越高。
如何实现对终端设备更为精准的定位成为亟需解决的问题。
发明内容
本申请实施例提供了一种确定位置的方法及设备，能够实现对终端设备的精准定位。
第一方面，提供了一种确定位置的方法，包括：根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与所述网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
第二方面，提供了一种通信设备，该通信设备可以执行上述第一方面或第一方面的任意可选的实现方式中的方法。具体地，该通信设备可以包括用于执行上述第一方面或第一方面的任意可能的实现方式中的方法的功能模块。
第三方面，提供了一种通信设备，包括处理器和存储器。该存储器用于存储计算机程序，该处理器用于调用并运行该存储器中存储的计算机程序，执行上述第一方面或第一方面的任意可能的实现方式中的方法。
第四方面，提供了一种芯片，用于实现上述第一方面或第一方面的任意可能的实现方式中的方法。具体地，该芯片包括处理器，用于从存储器中调用并运行计算机程序，使得安装有该芯片的设备执行如上述第一方面或第一方面的任意可能的实现方式中的方法。
第五方面，提供了一种计算机可读存储介质，用于存储计算机程序，该计算机程序使得计算机执行上述第一方面或第一方面的任意可能的实现方式中的方法。
第六方面，提供了一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行上述第一方面或第一方面的任意可能的实现方式中的方法。
第七方面，提供了一种计算机程序，当其在计算机上运行时，使得计算机执行上述第一方面或第一方面的任意可能的实现方式中的方法。
第八方面，提供了一种通信系统，包括通信设备，其中，该通信设备用于：根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与基站之间的伪距，所述第一终端设备与基站之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
本申请提供的技术方案，可以结合多个测量参数，来确定终端设备的位置，相比于仅采用单一的测量量进行定位的方案，能够提高定位精度。此外，本申请实施例还提供一种基于终端设备之间的伪距进行定位的方案，能够在没有基站或卫星辅助的情况下，也能实现对终端设备的定位。
附图说明
图1是本申请实施例提供的一种车联网通信模式的示意性图。
图2是本申请实施例提供的另一种车联网通信模式的示意性图。
图3是本申请实施例提供的一种天线阵列进行角度测量的示意性结构图。
图4是本申请实施例提供的一种确定位置的方法的示意性流程图。
图5是本申请实施例的一种通信设备的示意性框图。
图6是本申请实施例的另一种通信设备的示意性结构图。
图7是本申请实施例的芯片的示意性结构图。
图8是本申请实施例的通信系统的示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，GSM)系统、码分多址(Code Division Multiple Access，CDMA)系统、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)系统、通用分组无线业务(General Packet Radio Service，GPRS)、长期演进(Long Term Evolution，LTE)系统、LTE频分双工(Frequency Division Duplex，FDD)系统、LTE时分双工(Time Division Duplex，TDD)、通用移动通信系统(Universal Mobile Telecommunication System，UMTS)、全球互联微波接入(Worldwide Interoperability for Microwave Access，WiMAX)通信系统或5G系统等。
本申请实施例提到的网络设备可以是与终端设备(或称为通信终端、终端)通信的设备。网络设备可以为特定的地理区域提供通信覆盖，并且可以与位于该覆盖区域内的终端设备进行通信。可选地，该网络设备110可以是GSM系统或CDMA系统中的基站(Base Transceiver Station，BTS)，也可以是WCDMA系统中的基站(NodeB，NB)，还可以是LTE系统中的演进型基站(Evolutional Node B，eNB或eNodeB)，或者是新无线系统中的基站(gNB)，或者是云无线接入网络(Cloud Radio Access Network，CRAN)中的无线控制器，或者该网络设备可以为移动交换中心、中继站、接入点、车载设备、可穿戴设备、集线器、交换机、网桥、路由器、5G网络中的网络侧设备或者未来演进的公共陆地移动网络(Public Land Mobile Network，PLMN)中的网络设备等。
本申请实施例提及的终端设备可以是任何需要确定位置信息的终端设备。该终端设备可以指接入终端、用户设备(User Equipment，UE)、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置。接入终端可以是蜂窝电话、无绳电话、会话启动协议(Session Initiation Protocol，SIP)电话、无线本地环路(Wireless Local Loop，WLL)站、个人数字处理(Personal Digital Assistant，PDA)、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备、5G网络中的终端设备或者未来演进的PLMN中的终端设备等。
该终端设备可以是车联网中的车载终端，车联网中对车辆的位置精度要求非常高。车辆需要准确地确定出自己的当前位置，才能更好地实现无人驾驶。
终端设备在各种场景中，都需要进行定位，以更好地实现终端设备的功能。例如，终端设备的导航系统，终端设备需要准确地定位出当前的位置，以为用户规划合理的导航路线，提高用户体验。
本申请实施例可以适用于任何终端设备到终端设备的通信框架。
例如，车辆到车辆(vehicle to vehicle，V2V)、车辆到其他设备(vehicle to everything，V2X)、设备到设备(device to device，D2D)等。
下面对本申请实施例的应用场景进行介绍，主要以车联网为例进行介绍。
可选地，在本申请的一些实施例中，本申请实施例可以适用于第三代合作伙伴计划(3rd  generation partnership project，3GPP)Rel-14中定义的传输模式3和传输模式4。
图1是本申请实施例的模式3的示意图。图2是本申请实施例的模式4的示意图。
在图1所示的传输模式3中，车载终端(车载终端121和车载终端122)的传输资源是由基站110分配的，车载终端根据基站110分配的资源在侧行链路上进行数据的发送。具体地，基站110可以为终端分配单次传输的资源，也可以为终端分配半静态传输的资源。
在图2所示的传输模式4中，车载终端(车载终端131和车载终端132)采用侦听(sensing)加预留(reservation)的传输方式，车载终端在侧行链路的资源上自主选取传输资源进行数据传输。
车辆在车联网系统中，需要实时地确定当前位置，避免与其他物体发生碰撞。
目前，普遍使用的定位方式是使用基站进行定位，或者是使用卫星进行定位。
基站定位可以是基于观测到达时间差(observed time difference of arrival，OTDOA)进行定位。卫星定位可以是基于双曲线定位算法进行定位。这两种定位方式原理相同，下面以卫星为例说明其算法。
一般情况下，卫星可以向终端设备发送一个信号，终端设备可以根据该信号的接收时间，以及卫星发射该信号的时间，确定信号到达时间差；根据信号到达时间差，确定终端设备与卫星之间的测量距离。终端设备在确定信号到达时间差时，由于终端设备的时钟与卫星的时钟不同步，存在时钟偏差，或者在信号传输过程中，由于信号噪声、时钟噪声等因素的影响，使得终端设备确定的信号到达时间差并不等于真实的信号传输时间，从而由该到达时间差计算出的距离也并非是终端设备与卫星之间的真实距离，我们可以将该测量距离称为伪距。
本申请实施例可以根据终端设备与卫星之间的伪距来确定终端设备的位置。例如，可以以某一卫星为参考卫星，其他卫星的伪距减去参考卫星的伪距可以得到两个卫星伪距的差。由于做差能够消去终端设备的时钟偏差的影响，因此伪距的差可以更真实地近似两个卫星到终端设备的距离差。进一步地，可以通过对该多个距离差做最小二乘代价函数，采用一阶近似的泰勒算法可以获得车辆的位置估计。
但是，随着5G技术的发展，终端设备对定位精度的要求越来越高。尤其是在车联网系统中，对定位精度的要求更为严格。
上述最小二乘代价函数不够精确，且直接采用一阶近似的泰勒算法进行定位，这会导致当测量误差较大时容易收敛到错误的位置，从而计算的终端设备的位置与实际位置之间的误差较大，定位精度不高。
另外，卫星系统由于其特殊的高空特性，只能实现米级的二维平面精度，而高度上的定位精度很差，达到十米级。基站在高度上的定位精度虽然高于卫星，但是基站容易被遮挡，导致能够被车辆获取的数目有限，车辆不能使用被遮挡的基站进行定位；且基站存在同频干扰，远处的基站信号容易被近处的基站信号干扰，故基站的定位精度也有限，大致在十米级。传统定位算法仅依靠单一的卫星系统或基站系统，只考虑单一的测量量，例如基站的伪距或卫星的伪距。由于测量量较少，不能发挥卫星和基站两者不同的优势，无法满足车联网亚米级的精度要求。
此外，基站端的天线阵列可以测角度，以及终端设备之间也可以相互协作测量，这些能够提高系统精度的测量项都没有加入到现有的算法中。基于此，本申请实施例提供一种确定位置的方法，能够提高终端设备的定位精度。
如图3所示，该确定位置的方法包括步骤S210。
S210、根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
该第一终端设备可以是车联网系统中的车载终端，如车辆；也可以是其他网络的终端设备，例如移动终端等，本申请实施例对该第一终端设备的类型不做具体限定。
本申请实施例中的第二终端设备可以表示除第一终端设备之外的其他任意终端设备。
本申请实施例中的网络设备例如可以是基站。为方便理解，下文以网络设备为基站为例进行描述。
该第一参数为通过测量得到的参数，如伪距测量值和角度测量值。对于某些终端设备来说，其也可以实现对终端设备的角度测量，对于这种情况，第一参数中也可以包括终端设备之间的角度测量值。
本申请实施例提供的技术方案，可以将基站系统、卫星系统和终端网络系统中的测量量融合起来，进行终端设备的定位，相比于采用单一的测量量方案，能够提升定位精度。
此外，第一参数也可以仅包括上述参数中的一种参数，例如，第一参数可以仅包括终端设备之间的伪距，或者仅包括第一终端设备与基站之间的角度。通过该第一参数，也可以确定出第一终端设备的位置。
第一终端设备的位置可以是绝对位置，也可以是相对位置。绝对位置可以指第一终端设备在经纬度坐标，相对位置可以是指第一终端设备相对于其他终端设备的位置。
第一终端设备的位置信息可以包括第一终端设备的三维位置信息，或者二维位置信息，本申请实施例对此不做限定。
为方便描述，本申请实施例可以将终端设备、卫星和基站统称为节点。第一终端设备与节点之间的伪距可以采用传统的测量伪距的方法进行获得。
本申请实施例中的卫星可以是全球定位系统(global positioning system，GPS)卫星，也可以是北斗卫星等，对此不做限定。
本申请实施例中的基站可以是5G系统中的基站，也可以是LTE系统中的基站，或者其他系统中的基站。
第一终端设备与基站之间的角度可以是指基站的天线阵列测得的基站与第一终端设备之间的角度。第一终端设备与基站之间的角度可以包括第一终端设备与基站之间的方位角和/或俯仰角。
本申请实施例对确定第一终端设备的位置方式不做具体限定。假设第一参数包括第一终端设备与卫星之间的伪距，以及第一终端设备与基站之间的伪距。
作为一个示例，确定位置的方式可以是指，根据第一终端设备与卫星之间的伪距，以及第一终端设备与基站之间的伪距，分别计算出第一终端设备的位置，也就是说，可以根据第一终端设备与卫星之间的伪距计算出第一终端设备的位置X1，然后根据第一终端设备与基站之间的伪距计算出第一终端设备的位置X2，最后可以根据位置X1和位置X2，最终确定出第一终端设备的位置。
根据位置X1和位置X2，确定第一终端设备的位置可以指，将位置X1和位置X2的平均值作为第一终端设备的位置。或者，也可以对位置X1和位置X2分别设置不同的权重，计算出第一终端设备的位置。
本申请实施例对根据第一终端设备与卫星之间的伪距，计算第一终端设备的位置X1的方式不做限定。例如可以采用传统的最小二乘代价函数，确定第一终端设备的位置X1；或者也可以根据双曲线定位算法确定第一终端设备的位置X1。
类似的，根据第一终端设备与基站之间的伪距，计算第一终端设备的位置X2的方式也可以采用上述方式中的任意一种。
作为又一示例，确定位置的方式也可以是将第一终端设备与卫星之间的伪距，以及第一终端设备与基站之间的伪距融合在一个代价函数中，通过对该代价函数进行迭代，确定出第一终端设备的位置。
为方便描述，将第一终端设备与卫星之间的伪距简称为卫星的伪距，将第一终端设备 与基站之间的伪距简称为基站的伪距。
上文是以卫星的伪距和基站的伪距进行举例说明的，本申请实施例的第一参数也可以包括其他的参数，例如第一终端设备与基站的之间角度，和/或第一终端设备与其他终端设备之间的伪距。
当然，第一参数还可以包括其他的测量量，例如，在终端设备与终端设备之间可以进行角度测量的情况下，也可以根据终端设备之间的角度进行定位。任何可以进行位置确定的参数都可以包含在第一参数之内。
本申请实施例还可以为不同的参数分别设置权重。也就是说，第一参数中的每个参数分别具有各自的权重信息，不同参数的权重可以相同，也可以不同，具体的权重信息可以根据实际情况来确定。本申请实施例可以根据第一参数，以及第一参数中每个参数的权重信息，确定第一终端设备的位置。
这种确定位置的方式，可以根据具体情况，为不同的参数设置不同的权重。例如，在测量参数相对准确的情况下，可以为该参数设置较高的权重，在测量参数误差较大的情况下，为该参数设置较低的权重，这样在根据多个参数确定第一终端设备的位置时，能够保证第一终端设备位置的精度。
除了时钟偏差的影响外，距离的偏差主要是由于噪声而产生的，噪声可以包括信号噪声和/或时钟噪声。由于噪声不可消除，也不可避免，因此在确定终端设备位置时，我们可以尽量减小噪声的影响。作为一种实现方式，可以基于噪声来为不同的参数设置不同的权重，以提高定位精度。
假设第一终端设备与卫星之间的伪距具有第一权重，第一终端设备与基站之间的伪距具有第二权重，第一终端设备与第二终端设备之间的伪距具有第三权重，第一终端设备与基站之间的角度具有第四权重。
由于卫星的时钟相对稳定，因此可以不用考虑卫星的时钟噪声的影响，在确定权重时可以根据信号噪声的方差来确定第一权重。对于基站和第二终端设备来说，可能会存在时钟噪声的影响，因此，第二权重和第三权重可以是根据信号噪声的方差和时钟噪声的方差共同确定的。基站测量的与第一终端设备之间的角度也会受到信号噪声的影响，因此，第四权重可以是根据信号噪声的协方差确定的。
作为一种实现方式，第一权重可以为信号噪声的方差的倒数，第二权重和第三权重可以为信号噪声的方差和时钟噪声的方差之和的倒数，第四权重可以为信号噪声协方差的逆矩阵。
可选地，第一终端设备与第二终端设备之间的伪距可用于确定距离估计值，该距离估计值可以为第一终端设备获得的与第二终端设备之间的伪距，以及第二终端设备获得的与第一终端设备之间的伪距的均值；则根据第一参数，确定一终端设备的位置可以指，根据该距离估计值，确定第一终端设备的位置。
本申请实施例利用终端设备之间可以进行双向测距的特性，在进行定位时，采用双向测距的均值(即距离估计值)作为第一参数进行计算，由于距离估计值能够消去终端设备的时钟偏差的影响，因此距离估计值能够更真实地反映两个终端设备之间的距离，从而采用距离估计值进行定位也能够提高定位精度。
可选地，本申请实施例对确定第一终端设备的位置所采用的算法不做限定。例如，可以是基于最大似然理论，构建最大似然函数，通过该最大似然函数确定第一终端设备的位置。下文将会对该最大似然函数进行详细描述。
该最大似然函数中还可以包括时钟偏差参数，本申请在确定终端设备位置的同时，也能够将终端设备的时钟偏差确定出来。具体地，可以根据第一参数，以及最大似然函数，计算出第一终端设备的时钟偏差。
对最大似然函数进行计算，确定终端设备的位置可以是由终端设备、基站和卫星中的 任意一个节点执行的。
该似然函数可以是集中式似然函数，表示所有终端设备的位置信息都是由同一个计算节点对该似然函数进行迭代得到的。
或者，该似然函数可以是分布式似然函数，表示每个终端设备仅计算自己的位置信息。多个终端设备的位置可以是多个终端设备中的每个终端设备分别对该似然函数进行迭代得到的。
第一终端设备根据第一参数，以及最大似然函数，确定第一终端设备的位置可以指，第一终端设备可以根据第一参数，对该似然函数进行迭代，得到第一终端设备的第m次迭代参数，m为大于或等于1的整数；然后可以根据多个终端设备中其他终端设备的第m次迭代参数和第一终端设备的第m次的迭代参数，确定第一终端设备的第(m+1)次迭代参数；重复上述步骤，直到所有的迭代参数都不再发生变化，或者达到最大迭代次数；根据最后一次的迭代参数，确定第一终端设备的位置。
下面结合具体的例子，对本申请实施例提供的最大似然函数进行详细描述。
我们可以假设系统中有N c个终端设备，N b个基站，N s个卫星，其中，基站和卫星的位置是已知的。该N c个终端设备可以计算出与N b个基站之间的伪距，和/或与N s个卫星之间的伪距。终端，基站和卫星的集合定义如下：
Figure PCTCN2019076775-appb-000001
和
Figure PCTCN2019076775-appb-000002
Figure PCTCN2019076775-appb-000003
该终端设备可以是车辆，N c个终端设备可以指车联网系统中的N c个车辆。
节点k(包括终端设备、基站和卫星)的位置记为p k＝[x k,y k,z k] T，包含所有终端设备位置的参数向量记为
Figure PCTCN2019076775-appb-000004
我们可以定义参数a的测量形式和估计形式分别为
Figure PCTCN2019076775-appb-000005
和
Figure PCTCN2019076775-appb-000006
本申请实施例可以假设卫星和基站是同步的，也就是说，卫星和基站之间没有时钟偏差。终端设备k由于硬件设备的限制，与基站和卫星之间存在时钟偏差δ k。
定义节点k观察节点j的距离d kj，俯仰角θ kj，和方位角φ kj分别为：
d kj＝||p k-p j||
Figure PCTCN2019076775-appb-000007
Figure PCTCN2019076775-appb-000008
其中，p k表示节点的位置，p j表示节点j的位置。
节点k可以接收来自节点j的信号，节点k例如可以是第一终端设备，节点j可以是卫星、基站、其他终端设备中的任一种。
节点k可以接收到来自节点j的信号，该信号可以写成如下形式：
r kj(t)＝α kjs j(t-τ kj)+n kj(t)               (2)
其中，s j(t)是已知信号，其傅里叶变换为S j(f)，α kj和τ kj分别是节点j到节点k传输链路的信号幅度和时延，n kj(t)是功率谱密度为N 0/2的高斯白噪声。也就是说，节点k接收到的信号除了节点j发送的s j(t)信号之外，还会包括噪声信号n kj(t)。
假设节点j为卫星，对于节点k接收到来自卫星j的信号，我们采用以下伪距模型，伪距测量值
Figure PCTCN2019076775-appb-000009
建模如下：
Figure PCTCN2019076775-appb-000010
其中，
Figure PCTCN2019076775-appb-000011
表示节点k与节点j之间的伪距，d kj表示节点k与节点j之间的实际距离，b k表示节点k的时钟偏差引入的距离偏差，ω kj是由于信号噪声n kj(t)引入的一个等效零均值高斯误差，换句话说，ω kj是由于信号噪声n kj(t)引入的距离误差。
其中，b k＝c*δ k，c为光速，δ k表示节点k(或称终端设备k)的时钟偏差。
ω kj的方差
Figure PCTCN2019076775-appb-000012
满足：
Figure PCTCN2019076775-appb-000013
本申请实施例可以基于ω kj的方差可用于确定节点k与节点j之间的伪距的权重。例如，可以将方差
Figure PCTCN2019076775-appb-000014
的倒数确定为节点k与节点j之间伪距的权重。
从上式可以看出，该方差和信噪比、等效带宽成反比，可以通过增加信噪比和等效带宽来减小方差。
假设节点j为基站或其他终端设备，对于节点k接收到来自节点j的信号，我们还考虑了终端设备和基站的时钟漂移等引起的时钟噪声的影响。因此，可以建立以下伪距模型：
Figure PCTCN2019076775-appb-000015
其中，b j表示节点j的时钟偏移引入的距离偏差，υ kj表示时钟噪声引入的距离误差。时钟噪声若不进行校准，其方差
Figure PCTCN2019076775-appb-000016
会随着时间的累积而增长。该时钟噪声的方差
Figure PCTCN2019076775-appb-000017
可以在时钟的出厂参数中获得。
对于节点j为基站的情况，我们可以假设基站与卫星同步，不存在时钟偏移，此时b j＝0。此时，伪距模型可以表示为：
Figure PCTCN2019076775-appb-000018
对于不同的伪距测量，我们引入参数λ kj，其表示两种噪声叠加后方差的倒数：
对于节点j为卫星的情况：
Figure PCTCN2019076775-appb-000019
对于节点j为基站或其他终端设备的情况：
Figure PCTCN2019076775-appb-000020
除了上述伪距测量量之外，本申请实施例还考虑了基站可以测角的性质，基站j可以测量与终端设备k之间的俯仰角θ jk和方位角φ jk，其建模可以如下：
Figure PCTCN2019076775-appb-000021
其中，
Figure PCTCN2019076775-appb-000022
表示节点j与节点k之间的俯仰角的测量值，
Figure PCTCN2019076775-appb-000023
表示节点j与节点k之间的方位角的测量值，θ jk表示节点j与节点k之间的实际俯仰角，φ jk表示节点j与节点k之间的实际方位角，μ jk表示由于信号噪声引入的二维角度上的等效零均值的高斯噪声，其协方差矩阵可以用C jk来表示。
C jk的具体形式与基站天线阵列的空间结构有关，基站天线阵列的空间结构例如可以是矩形阵列或圆形阵列等。对于不同的空间结构，C jk的表达形式不同。下面以基站的天线阵列为矩形阵列为例进行说明，如图4所示，假设基站的天线阵列为M×N的矩形阵列。
以图4所示的天线阵列进行角度测量时，可令
Figure PCTCN2019076775-appb-000024
Figure PCTCN2019076775-appb-000025
Δ为图中阵元间隔，或者，Δ可以理解为行间距或列间距，λ为信号波长，则μ jk的协方差矩阵C jk可以表示为：
Figure PCTCN2019076775-appb-000026
其中：
a＝cos 2θ jk(mcos 2φ jk+nsin 2φ jk+2lcosφ jksinφ jk)
b＝cosθ jksinθ jk((n-m)cosφ jksinφ jk+l(cos 2φ jk-sin 2φ kj))
d＝sin 2θ jk(msin 2φ jk+ncos 2φ jk-2lcosφ jksinφ jk)
建立伪距模型和角度模型后，我们可以通过合适的算法得到终端设备的位置信息。
例如，可以通过传统算法计算出终端设备的位置。又例如，也可以基于本申请实施例提供的最大似然函数计算出终端设备的位置。
基于最大似然理论，我们可以构造出如下总似然函数，其中，z是所有测量组成的向量。p表示所有终端设备的位置组成的向量，b表示所有终端设备的时钟偏移组成的向量。
Figure PCTCN2019076775-appb-000027
其中，p k表示节点k的位置，节点k可以是终端设备，p j表示节点j的位置，节点j可以是终端设备、基站和卫星中的任意一种，‖p k-p j‖表示节点k与节j之间的实际距离。
Figure PCTCN2019076775-appb-000028
上式表示基站或卫星的伪距的最大似然。
Figure PCTCN2019076775-appb-000029
上式表示终端设备之间的伪距的最大似然。
Figure PCTCN2019076775-appb-000030
上式表示基站与终端设备之间的角度的最大似然。
本申请实施例在确定终端设备的位置时，考虑了多个测量项，并且可以将多个测量项集成在一个代价函数中，通过对该代价函数进行多次迭代，直至所述代价函数收敛或者达到最大迭代次数，然后可以将最后一次的迭代参数确定为终端设备的位置。
其次，本申请实施例提供的似然函数中还考虑了时钟偏差的影响，将时钟偏差产生的距离偏差也引入到似然函数中进行计算，在计算出终端设备位置的同时，也能获得终端设备的时钟偏差。该时钟偏差可以在终端设备后续的通信过程中具有重要的作用，例如，终端设备可以将自己的时钟偏差告诉给对端终端设备，这样有利于后续的通信。
当然，本申请实施例的似然函数也不局限于上述形式，例如，也可以不考虑时钟偏差带来的距离偏差，直接通过测量的伪距进行位置估计。
进一步地，本申请实施例还考虑终端设备之间可以进行双向测距的特性，也就是说，第一参数可以包括第一终端设备获得的与第二终端设备之间的伪距，以及第二终端设备获得的与第一终端设备之间的伪距。因此将第一终端设备与第二终端设备之间测得的双向伪距都进行考虑，集成到该似然函数中，能够进一步提高定位精度。
第一终端设备k获得的与第二终端设备j之间的伪距可以指，第二终端设备j可以向第一终端设备发送第一信号，该第一信号中可以包括第二终端设备j发送第一信号的发送时间t1，第一终端设备k接收到第一信号之后，可以根据自己的接收时间t2，确定出与第二终端设备j之间的伪距为
Figure PCTCN2019076775-appb-000031
第二终端设备j获得的与第一终端设备k之间的伪距可以指，第一终端设备k可以向第二终端设备j发送第二信号，该第二信号中可以包括第一终端设备k发送第二信号的发送时间t3，第二终端设备j接收到第二信号之后，可以根据自己的接收时间t4，确定出与第一终端设备k之间的伪距为
Figure PCTCN2019076775-appb-000032
此时，在考虑了终端设备之间的双向测距的特性后，最大似然函数中的终端设备之间的伪距的最大似然可以变形为：
Figure PCTCN2019076775-appb-000033
Figure PCTCN2019076775-appb-000034
表示节点k获得的与节点j之间的伪距的最大似然，
Figure PCTCN2019076775-appb-000035
表示节点j获得的与节点k之间的伪距的最大似然。
进一步地，本申请实施例还可以为不同的参数设置不同的权重，对于卫星的伪距，我们可以仅考虑信号噪声的影响，因此可以基于信号噪声为卫星的伪距设置权重，例如，将信号噪声的方差的倒数λ kj设置为卫星伪距的权重，
Figure PCTCN2019076775-appb-000036
节点j表示卫星。
对于基站的伪距，我们可以同时考虑信号噪声和时钟噪声的影响，基站的伪距可以是根据信号噪声的方差和时钟噪声的方差共同确定的，例如，基站伪距的权重可以为信号噪声的方差和时钟噪声的方差之和的倒数，
Figure PCTCN2019076775-appb-000037
节点j表示基站。
对于终端设备之间的伪距，与基站的伪距类似，我们可以同时考虑信号噪声和时钟噪声的影响，为终端设备之间的伪距设置权重，该权重例如可以为
Figure PCTCN2019076775-appb-000038
节点j表示其他终端设备。
对于基站的角度测量，本申请实施例可以考虑信号噪声引入的二维角度上的等效零均值高斯噪声的影响，该信号噪声的协方差矩阵可用于确定角度测量的权重。例如，将协方差矩阵的逆矩阵确定为角度测量的权重。
我们可以将上述权重信息添加到最大似然函数中，进行终端设备位置的确定。
该最大似然函数可以变形为：
Figure PCTCN2019076775-appb-000039
上述似然函数中，可以为不同的参数设置不同的权重λ kj。
由于噪声的方差与信噪比成反比，而λ kj与噪声的方差成反比，因此，λ kj与信噪比成正比，也就是说，信噪比越大，权重λ kj也越大。如果一个测量量的信噪比比较大，表示该信号中的噪声较小，则可以为该测量量赋予较大的权重；如果一个测量量的信噪比比较小，表示该信号中的噪声比较大，则可以为该测量量赋予较小的权重。这种设置权重的方式较为合理，在算法中考虑了信号噪声和时钟噪声的影响，由该最大似然函数确定的终端设备的位置也与实际位置比较接近，定位精度较高。
对于上述最大似然函数，本申请实施例对其求解所采用的方式不做具体限定。例如，可以是梯度下降法，EM算法、坐标上升或下降算法等。下面以梯度下降算法为例，对似然函数的求解过程进行描述。
对于上述似然函数，我们的目的是找到合适的P和b，使得上述似然函数值最大。因为该似然函数为指数形式，因此我们只需得到指数项的最大值，就可以获得该似然函数的最大值。也就是说，让下述代价函数H(p,b)值最小。
Figure PCTCN2019076775-appb-000040
H(p,b)表现为加权平方和的形式。其中，包含了两部分内容，一部分是来自锚点的信息，例如来自基站的伪距和角度信息，来自卫星的伪距信息。另一部分是来自其他终端设备的伪距信息。其中，
Figure PCTCN2019076775-appb-000041
是测量得到的伪距值和角度值。我们的目的是让解算的伪距和角度值，与测量的伪距和角度值之间的偏差最小。
对于上述似然函数，由于其包括所有的测量信息，也就是说，包括N c个终端设备、N b个基站和N s个卫星之间的所有节点之间的测量信息，因此我们可以将该似然函数称为集中式定位算法。
采用梯度下降算法进行求解时，我们可以给出H(p,b)中每个多项式对于P和b的梯度(即一阶导数)。对于H(p,b)中的每个多项式，其只表示节点j和节点k之间的测量，故只和终端设备的未知参数p j,p k,b j,b k有关。
对于伪距测量，我们以终端设备之间的伪距测量为例进行说明，基站或卫星之间的伪距对于终端设备的位置参数p k和时钟偏差参数b k的一阶导数也可以通过下式类比得到，只需将多项式中的p j,b j当成是相应的卫星或基站的已知参数即可。
对终端设备之间的伪距的测量项，我们对其进行求导，可以得到：
Figure PCTCN2019076775-appb-000042
Figure PCTCN2019076775-appb-000043
Figure PCTCN2019076775-appb-000044
Figure PCTCN2019076775-appb-000045
对于基站和终端设备之间的角度测量，首先定义：
Figure PCTCN2019076775-appb-000046
则角度测量项对应的梯度为：
Figure PCTCN2019076775-appb-000047
得到各多项式的一阶导数后，可以对似然函数进行第一次迭代，得到该第一次迭代的最小值。进一步地，根据第一次迭代的迭代参数进行第二次迭代，得到该第二次迭代的迭代参数。依次循环，直至迭代参数不再发生变化，或者达到最大迭代次数。
在对该似然函数进行求解时，可以输入终端设备和所有节点之间的伪距和角度测量值。然后可以给定所有终端设备的初始状态
Figure PCTCN2019076775-appb-000048
和
Figure PCTCN2019076775-appb-000049
并根据该初始状态进行迭代。对于第m次的迭代参数
Figure PCTCN2019076775-appb-000050
和
Figure PCTCN2019076775-appb-000051
可以根据整体代价函数和当前的迭代参数
Figure PCTCN2019076775-appb-000052
和
Figure PCTCN2019076775-appb-000053
根据上述给出的梯度表达式计算位置和时钟参数的梯度，依据梯度下降更新下一轮的参数
Figure PCTCN2019076775-appb-000054
和
Figure PCTCN2019076775-appb-000055
m为大于等于1的整数。直至该似然函数收敛或者达到最大迭代次数；根据最后一次迭代对应的迭代参数，确定终端设备的位置和时钟偏差。
除了上述确定权重的方式之外，还可以是其他的确定权重的方式。作为一种实现方式，可以给每个测量量设置固定的权重信息，例如，卫星的伪距、基站的伪距、基站的角度、终端设备之间的伪距的权重可以分别为0.3、0.3、0.2、0.2。
上述计算过程是假设所有的测量项都存在的情况下进行描述的。当然，可以可以只有其中部分测量项，对于只有部分测量项的情况下，上述似然函数及其计算过程也同样适用，只需将测量缺失的测量项置为0即可。
对于没有基站或卫星系统的测量项的情况下，也就是说，没有基站或卫星辅助定位，第一参数值仅包括终端设备的伪距的情况下，如果直接采用上述给定的梯度下降算法进行定位，若给定的初值不够好，容易产生不收敛或者收敛到错误位置的情况，即计算得到的终端设备的位置与实际位置相差很大。
由于无卫星和基站辅助，此时可以以第一个车辆为时钟基准，令其时钟偏差引入的距离偏差b 1＝0，然后可以根据双向测量得到终端设备之间的距离估计值，以及其他车辆相对于第一个车辆的时钟偏差。
由于式(5)是关于距离d kj以及偏差b k,b j的线型模型，故直接采用最小二乘即可得到所有距离d kj和距离偏差b k的估计。
本申请实施例还提供另外一种简单的获得距离估计的方式，即对双向测距直接进行平均，得到距离估计值：
Figure PCTCN2019076775-appb-000056
采用距离估计值进行定位，可以消去第一终端设备与第二终端设备的时钟偏差对距离估计的影响。
获得所有节点之间的距离估计值后，可直接通过经典的多维标定算法即可得到终端设备网络的形状，或者也可以通过其他算法例如半正定规划算法来获得终端设备网络的“形状估计”。下面以多维标定算法为例进行说明，平方距离矩阵
Figure PCTCN2019076775-appb-000057
的k行j列可以表示为：
Figure PCTCN2019076775-appb-000058
对于平方距离矩阵
Figure PCTCN2019076775-appb-000059
中没有测量的距离值，可以采用经典的最短路径算法进行代替。然后对平方距离矩阵
Figure PCTCN2019076775-appb-000060
可以采用多维标定算法即可获得终端设备网络的“形状”。
多维标定算法的实现可以如下：
首先对平方距离矩阵
Figure PCTCN2019076775-appb-000061
去质心化，得到G矩阵。
Figure PCTCN2019076775-appb-000062
其中L＝I-1/N c11 T,I为N c维单位阵，1为N c维全为1的列向量。对G矩阵进行特征值分解得到特征值和其对应的特征向量。取出最大的三个特征值和其对应的特征向量分别相乘得到三个加权的向量，按特征值从大到小顺序排列三个向量得到一个三列的矩阵，即为三维位置参数矩阵。如果只需要二维位置矩阵，则只取该三列矩阵的前两列即可。
上述集中式定位算法需要集合网络中的所有测量，且所有的这些测量量都需要在一个中心点集中计算，也就是说，所有终端设备的位置以及时钟偏差都是通过一个中心点进行计算得到的。该中心点可以是终端设备、基站和卫星中的任意一个节点。该算法由于直接对N c个车辆的p和b进行解算，解算空间大导致复杂度高，对于中心点的计算能力也有很高的要求。
另外，在移动网络中，为了保持实时性，很多时候无法将所有的数据都收集到中心节点进行计算，并且大部分节点的计算能力也无法实时计算出所有节点的参数。
基于此，本申请实施例提供一种分布式定位算法，该算法可以将计算过程进行分解，每个终端设备k只需计算自己的位置p k和时钟偏差b k，这样也可以得到所有终端设备的位置和时钟偏移。这种计算方式能够降低计算节点的计算复杂度，能够提高计算速率，保证移动网络中的实时性要求。
对于分布式定位算法，我们可以从集中式代价函数H(p,b)中把和终端设备k有关的项提取出来，构造局部代价函数H k(p k,b k)，如下：
Figure PCTCN2019076775-appb-000063
每个终端设备均可以按照上文描述的求导方式，对似然函数进行迭代，每个终端设备对各自的似然函数进行迭代，求出其对应的位置和时钟偏移。具体的迭代过程如下：
第一终端设备可以根据第一参数，对该分布式似然函数进行迭代，得到该第一终端设备的第m次迭代参数，m为大于或等于1的整数。
第一终端设备可以接收其他终端设备广播的其他终端设备的第m次迭代参数，并根据其他终端设备的第m次迭代参数，利用梯度下降算法，得到本节点的第(m+1)次迭代参数。
重复上述步骤，直到所有的迭代参数不在发生变化，或者达到最大迭代次数。
第一终端设备根据最后一次的迭代参数，确定第一终端设备的位置和时钟偏移。例如，第一终端设备可以将最后一次迭代参数中的p确定为第一终端设备的位置信息，将最后一次迭代参数中的b确定为第一终端设备的时钟偏移距离。
同样地，第二终端设备可以采用上述步骤，得到第二终端设备的位置和时钟偏移。以此类推，每个终端设备都可以得到本节点的位置和时钟偏移。这样整个终端设备系统的位置和时钟偏移都可以获得到。
对于局部式定位算法，当无锚点时，也就是说，没有基站系统和卫星系统辅助定位时，可直接采用上文描述的梯度下降算法进行计算。但是，如果给定的初值不够好，也容易产生不收敛或收敛到错误位置的情况。
基于此，本申请实施例提供一种计算方式，可以避免不收敛或收敛到错误位置的情况。下面对该计算方式进行描述。
每个终端设备可以通过式(6)获得其和邻居的距离值，每个终端设备可以将其获得的所有距离值广播给其他终端设备。这样，每个终端设备都可以获得其1跳网络内的所有测量信息，也就是说，每个终端设备都可以获得能够与自己通信的其他终端设备的测量信息。终端设备可以根据该1跳范围内的所有节点的距离测量值(或称伪距)，根据多维标定算法或半正定规划算法，即可获得每个终端设备1跳网络的“形状”。进一步地，可以将这些局部的结构融合起来得到整个网络的“形状”。具体的计算过程如下：
输入为终端设备与其他终端设备之间的伪距，输出为整个终端设备网络的“形状”。
每个终端设备可以上文描述的多维标定算法构建自己第0轮迭代的本地的1跳网络“形状”
Figure PCTCN2019076775-appb-000064
并将其广播给邻居。
从任一终端设备开始，将其定为起始网络，这里以将终端设备k定义为起始网络为例。
对于第m次的迭代参数
Figure PCTCN2019076775-appb-000065
终端设备k可以从不在
Figure PCTCN2019076775-appb-000066
中的终端设备中挑选出终端设备j，使得
Figure PCTCN2019076775-appb-000067
和
Figure PCTCN2019076775-appb-000068
拥有的共有节点最多m为大于等于1的整数。
通过共有节点的空间关系将
Figure PCTCN2019076775-appb-000069
和
Figure PCTCN2019076775-appb-000070
融合成一个包含
Figure PCTCN2019076775-appb-000071
和
Figure PCTCN2019076775-appb-000072
所有节点的新网络“形状”，将融合后的网络更新为
Figure PCTCN2019076775-appb-000073
直至
Figure PCTCN2019076775-appb-000074
包含所有终端设备。当
Figure PCTCN2019076775-appb-000075
包含所有终端设备时，则将其定为网络的整体“形状”。
相比于3GPP定位算法中只含有伪距测量参数，且只使用单一种类的信息(如基站或卫星)，本申请实施例不仅加入了基站的角度测量和终端设备之间相互协作的伪距测量，且在算法中将所有的这些测量同一整合到了一个代价函数中，通过融合之后的代价函数进行定位，能够提升定位精度。
本申请实施例提供的最大似然函数具有包含性，对于未知的测量项，或没有进行的测量项，只需将测量缺失的部分置为0即可，仍然可以沿用该似然函数进行定位。例如，对于只有基站的角度测量和伪距测量的情况下，只需将有关卫星伪距的多项式和终端设备之间的伪距的多项式置为0，仅对基站的角度和伪距的多项式进行迭代，得到终端设备的位置信息。
本申请实施例提供的最大似然函数能够在实现对终端设备的定位的同时，也能够实现对终端设备的时钟偏移的估计。
另外，本申请实施例采用梯度下降算法对最大似然函数进行求解，由于使用梯度下降算法，迭代的过程中只需计算梯度即可。且该梯度部分有闭式表达式，复杂度较低。尤其是对于车联网这种实时性要求较高的网络来说，低复杂度能够满足其实时性要求。本申请实施例提供的分布式定位算法能够进一步降低计算复杂度，提高实时性。
上文详细描述了本申请实施例提供的确定位置的方法，下面结合图5-图8，详细描述本申请实施例的装置，装置实施例与方法实施例相互对应，因此未详细描述的部分可以参见前面各方法实施例。
图5是本申请实施例提供的一种通信设备500的示意性框图。图5所示的通信设备500可以是方法实施例中的发送端设备。该通信设备可以包括处理单元510。
处理单元510，用于根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与所述网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
可选地，所述第一参数中的每个参数分别具有各自的权重信息，所述处理单元510用于：根据所述第一参数，以及所述第一参数中每个参数的权重信息，确定所述第一终端设备的位置。
可选地，所述第一终端设备与所述卫星之间的伪距具有第一权重，所述第一终端设备与所述网络设备之间的伪距具有第二权重，所述第一终端设备与所述第二终端设备之间的伪距具有第三权重，所述第一终端设备与所述网络设备之间的角度具有第四权重，所述第一权重是根据信号噪声的方差确定的，所述第二权重和所述第三权重是根据信号噪声的方差和时钟噪声的方差确定的，所述第四权重是根据信号噪声的协方差确定的。
可选地，所述第一终端设备与所述网络设备之间的角度包括方位角和/或俯仰角。
可选地，所述第一终端设备与所述第二终端设备之间的伪距用于确定距离估计值，所述距离估计值为所述第一终端设备获得的与所述第二终端设备之间的伪距，以及所述第二终端设备获得的与所述第一终端设备之间的伪距的均值；所述处理单元510用于：根据所述距离估计值，确定所述第一终端设备的位置。
可选地，所述处理单元510用于：根据所述第一参数，以及最大似然函数，确定所述第一终端设备的位置。
可选地，所述通信设备用于获取多个终端设备的位置，所述多个终端设备包括所述第一终端设备，所述处理单元510用于：根据所述第一参数，采用梯度下降算法对所述最大似然函数进行多次迭代，得到所述最大似然函数的最小值；根据所述最大似然函数最小值处的迭代参数，确定所述多个终端设备的位置。
可选地，所述多个终端设备的位置是同一个计算节点对所述最大似然函数进行迭代得到的。
可选地，所述多个终端设备的位置是所述多个终端设备中的每个终端设备分别对所述最大似然函数进行迭代得到的，所述处理单元510用于：根据所述第一参数，对所述最大似然函数进行迭代，得到所述第一终端设备的第m次迭代参数，m为大于或等于1的整数；根据所述多个终端设备中其他终端设备的第m次迭代参数和所述第一终端设备的第m次迭代参数，确定所述第一终端设备的第(m+1)次迭代参数；重复上述步骤，直到所有的迭代参数不再发生变化；根据最后一次的迭代参数，确定所述第一终端设备的位置。
可选地，所述最大似然函数中还包括所述第一终端设备的时钟偏差参数，所述处理单元510用于：根据所述第一参数，以及所述最大似然函数，确定所述第一终端设备的时钟偏差。
可选地，所述第一参数包括所述第一终端设备与所述第二终端设备之间的伪距，所述处理单元510用于：根据所述第一终端设备与所述第二终端设备之间的伪距，确定平方距离矩阵；根据所述平方距离矩阵，通过多维标定算法或半正定规划算法确定所述第一终端设备的位置。
可选地，所述第一终端设备的位置包括所述第一终端设备的二维位置信息和/或三维位置信息。
应理解，该通信设备500可以执行上述方法中由通信设备执行的相应操作，为了简洁，在此不再赘述。该通信设备500例如可以是上文描述的终端设备、网络设备或卫星。
图6是本申请实施例提供的一种通信设备600示意性结构图。图6所示的通信设备600包括处理器610，处理器610可以从存储器中调用并运行计算机程序，以实现本申请实施例中的方法。
可选地，如图6所示，通信设备600还可以包括存储器620。其中，处理器610可以从存储器620中调用并运行计算机程序，以实现本申请实施例中的方法。
其中，存储器620可以是独立于处理器610的一个单独的器件，也可以集成在处理器610中。
可选地，如图6所示，通信设备600还可以包括收发器630，处理器610可以控制该收发器630与其他设备进行通信，具体地，可以向其他设备发送信息或数据，或接收其他设备发送的信息或数据。
其中，收发器630可以包括发射机和接收机。收发器630还可以进一步包括天线，天线的数量可以为一个或多个。
可选地，该通信设备600具体可为本申请实施例的终端设备，并且该通信设备600可以实现本申请实施例的各个方法中由通信设备实现的相应流程，为了简洁，在此不再赘述。
图7是本申请实施例的芯片的示意性结构图。图7所示的芯片700包括处理器710， 处理器710可以从存储器中调用并运行计算机程序，以实现本申请实施例中的方法。
可选地，如图7所示，芯片700还可以包括存储器720。其中，处理器77可以从存储器720中调用并运行计算机程序，以实现本申请实施例中的方法。
其中，存储器720可以是独立于处理器710的一个单独的器件，也可以集成在处理器710中。
可选地，该芯片700还可以包括输入接口730。其中，处理器710可以控制该输入接口730与其他设备或芯片进行通信，具体地，可以获取其他设备或芯片发送的信息或数据。
可选地，该芯片700还可以包括输出接口740。其中，处理器710可以控制该输出接口740与其他设备或芯片进行通信，具体地，可以向其他设备或芯片输出信息或数据。
可选地，该芯片可应用于本申请实施例中的终端设备，并且该芯片可以实现本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
应理解，本申请实施例提到的芯片还可以称为系统级芯片、系统芯片、芯片系统或片上系统芯片等。
应理解，本申请实施例的处理器可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法实施例的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器可以是通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器读取存储器中的信息，结合其硬件完成上述方法的步骤。
可以理解，本申请实施例中的存储器可以是易失性存储器或非易失性存储器，或者可以包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read-Only Memory，ROM)、可编程只读存储器(Programmable ROM，PROM)、可擦除可编程只读存储器(Erasable PROM，EPROM)、电可擦除可编程只读存储器(Electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(Static RAM，SRAM)、动态随机存取存储器(Dynamic RAM，DRAM)、同步动态随机存取存储器(Synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，DDR SDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(Synchlink DRAM，SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM，DR RAM)。应注意，本文描述的系统和方法的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
应理解，上述存储器为示例性但不是限制性说明，例如，本申请实施例中的存储器还可以是静态随机存取存储器(Static RAM，SRAM)、动态随机存取存储器(Dynamic RAM，DRAM)、同步动态随机存取存储器(Synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，DDR SDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(Synch Link DRAM，SLDRAM)以及直接内存总线随机存取存储器(Direct Rambus RAM，DR RAM)等等。也就是说，本申请实施例中的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
图8是根据本申请实施例的通信系统800的示意性框图。如图8所示，该通信系统800包括网络设备810和终端设备820。
可选地，该网络设备810可以用于实现上述方法中由网络设备实现的相应的功能，以及该网络设备810的组成可以如图5中的通信设备500所示，为了简洁，在此不再赘述。
可选地，该终端设备820可以用于实现上述方法中由终端设备实现的相应的功能，以及该终端设备820的组成可以如图5中的通信设备500所示，为了简洁，在此不再赘述。
本申请实施例还提供了一种计算机可读存储介质，用于存储计算机程序。可选的，该计算机可读存储介质可应用于本申请实施例中的网络设备，并且该计算机程序使得计算机执行本申请实施例的各个方法中由网络设备实现的相应流程，为了简洁，在此不再赘述。可选地，该计算机可读存储介质可应用于本申请实施例中的终端设备，并且该计算机程序使得计算机执行本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
本申请实施例还提供了一种计算机程序产品，包括计算机程序指令。可选的，该计算机程序产品可应用于本申请实施例中的网络设备，并且该计算机程序指令使得计算机执行本申请实施例的各个方法中由网络设备实现的相应流程，为了简洁，在此不再赘述。可选地，该计算机程序产品可应用于本申请实施例中的终端设备，并且该计算机程序指令使得计算机执行本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
本申请实施例还提供了一种计算机程序。可选的，该计算机程序可应用于本申请实施例中的网络设备，当该计算机程序在计算机上运行时，使得计算机执行本申请实施例的各个方法中由网络设备实现的相应流程，为了简洁，在此不再赘述。可选地，该计算机程序可应用于本申请实施例中的终端设备，当该计算机程序在计算机上运行时，使得计算机执行本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
应理解，本文中术语“系统”和“网络”在本文中常被可互换使用。本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
还应理解，在本发明实施例中，“与A相应(对应)的B”表示B与A相关联，根据A可以确定B。但还应理解，根据A确定B并不意味着仅仅根据A确定B，还可以根据A和/或其它信息确定B。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，该单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络 单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应所述以权利要求的保护范围为准。

Claims (30)

  1. 一种确定位置的方法，其特征在于，包括：
    根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与所述网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
  2. 根据权利要求1所述的方法，其特征在于，所述第一参数中的每个参数分别具有各自的权重信息，所述根据第一参数，确定第一终端设备的位置，包括：
    根据所述第一参数，以及所述第一参数中每个参数的权重信息，确定所述第一终端设备的位置。
  3. 根据权利要求2所述的方法，其特征在于，所述第一终端设备与所述卫星之间的伪距具有第一权重，所述第一终端设备与所述网络设备之间的伪距具有第二权重，所述第一终端设备与所述第二终端设备之间的伪距具有第三权重，所述第一终端设备与所述网络设备之间的角度具有第四权重，所述第一权重是根据信号噪声的方差确定的，所述第二权重和所述第三权重是根据信号噪声的方差和时钟噪声的方差确定的，所述第四权重是根据信号噪声的协方差确定的。
  4. 根据权利要求1-3中任一项所述的方法，其特征在于，所述第一终端设备与所述网络设备之间的角度包括方位角和/或俯仰角。
  5. 根据权利要求1-4中任一项所述的方法，其特征在于，所述第一终端设备与所述第二终端设备之间的伪距用于确定距离估计值，所述距离估计值为所述第一终端设备获得的与所述第二终端设备之间的伪距，以及所述第二终端设备获得的与所述第一终端设备之间的伪距的均值；
    所述根据所述第一参数，确定所述第一终端设备的位置，包括：
    根据所述距离估计值，确定所述第一终端设备的位置。
  6. 根据权利要求1-5中任一项所述的方法，其特征在于，所述根据第一参数，确定第一终端设备的位置，包括：
    根据所述第一参数，以及最大似然函数，确定所述第一终端设备的位置。
  7. 根据权利要求6所述的方法，其特征在于，所述方法用于获取多个终端设备的位置，所述多个终端设备包括所述第一终端设备，所述根据所述第一参数，以及最大似然函数，确定所述第一终端设备的位置，包括：
    根据所述第一参数，采用梯度下降算法对所述最大似然函数进行多次迭代，得到所述最大似然函数的最小值；
    根据所述最大似然函数最小值处的迭代参数，确定所述多个终端设备的位置。
  8. 根据权利要求7所述的方法，其特征在于，所述多个终端设备的位置是同一个计算节点对所述最大似然函数进行迭代得到的。
  9. 根据权利要求7所述的方法，其特征在于，所述多个终端设备的位置是所述多个终端设备中的每个终端设备分别对所述最大似然函数进行迭代得到的，所述根据所述第一参数，以及最大似然函数，确定所述第一终端设备的位置，包括：
    根据所述第一参数，对所述最大似然函数进行迭代，得到所述第一终端设备的第m次迭代参数，m为大于或等于1的整数；
    根据所述多个终端设备中其他终端设备的第m次迭代参数和所述第一终端设备的第m次迭代参数，确定所述第一终端设备的第(m+1)次迭代参数；
    重复上述步骤，直到所有的迭代参数不再发生变化；
    根据最后一次的迭代参数，确定所述第一终端设备的位置。
  10. 根据权利要求6-9中任一项所述的方法，其特征在于，所述最大似然函数中还包 括所述第一终端设备的时钟偏差参数，所述方法还包括：
    根据所述第一参数，以及所述最大似然函数，确定所述第一终端设备的时钟偏差。
  11. 根据权利要求1-10中任一项所述的方法，其特征在于，所述第一参数包括所述第一终端设备与所述第二终端设备之间的伪距，所述根据所述第一参数，确定所述第一终端设备的位置，包括：
    根据所述第一终端设备与所述第二终端设备之间的伪距，确定平方距离矩阵；
    根据所述平方距离矩阵，通过多维标定算法或半正定规划算法确定所述第一终端设备的位置。
  12. 根据权利要求1-11中任一项所述的方法，其特征在于，所述第一终端设备的位置包括所述第一终端设备的二维位置信息和/或三维位置信息。
  13. 一种通信设备，其特征在于，包括：
    处理单元，用于根据第一参数，确定第一终端设备的位置，所述第一参数包括以下参数中的至少两个参数：所述第一终端设备与卫星之间的伪距，所述第一终端设备与网络设备之间的伪距，所述第一终端设备与所述网络设备之间的角度，所述第一终端设备与第二终端设备之间的伪距，或所述第一参数包括所述第一终端设备与第二终端设备之间的伪距。
  14. 根据权利要求13所述的通信设备，其特征在于，所述第一参数中的每个参数分别具有各自的权重信息，所述处理单元用于：
    根据所述第一参数，以及所述第一参数中每个参数的权重信息，确定所述第一终端设备的位置。
  15. 根据权利要求14所述的通信设备，其特征在于，所述第一终端设备与所述卫星之间的伪距具有第一权重，所述第一终端设备与所述网络设备之间的伪距具有第二权重，所述第一终端设备与所述第二终端设备之间的伪距具有第三权重，所述第一终端设备与所述网络设备之间的角度具有第四权重，所述第一权重是根据信号噪声的方差确定的，所述第二权重和所述第三权重是根据信号噪声的方差和时钟噪声的方差确定的，所述第四权重是根据信号噪声的协方差确定的。
  16. 根据权利要求13-15中任一项所述的通信设备，其特征在于，所述第一终端设备与所述网络设备之间的角度包括方位角和/或俯仰角。
  17. 根据权利要求13-16中任一项所述的通信设备，其特征在于，所述第一终端设备与所述第二终端设备之间的伪距用于确定距离估计值，所述距离估计值为所述第一终端设备获得的与所述第二终端设备之间的伪距，以及所述第二终端设备获得的与所述第一终端设备之间的伪距的均值；
    所述处理单元用于：
    根据所述距离估计值，确定所述第一终端设备的位置。
  18. 根据权利要求13-17中任一项所述的通信设备，其特征在于，所述处理单元用于：
    根据所述第一参数，以及最大似然函数，确定所述第一终端设备的位置。
  19. 根据权利要求18所述的通信设备，其特征在于，所述通信设备用于获取多个终端设备的位置，所述多个终端设备包括所述第一终端设备，所述处理单元用于：
    根据所述第一参数，采用梯度下降算法对所述最大似然函数进行多次迭代，得到所述最大似然函数的最小值；
    根据所述最大似然函数最小值处的迭代参数，确定所述多个终端设备的位置。
  20. 根据权利要求19所述的通信设备，其特征在于，所述多个终端设备的位置是同一个计算节点对所述最大似然函数进行迭代得到的。
  21. 根据权利要求19所述的通信设备，其特征在于，所述多个终端设备的位置是所述多个终端设备中的每个终端设备分别对所述最大似然函数进行迭代得到的，所述处理单元用于：
    根据所述第一参数，对所述最大似然函数进行迭代，得到所述第一终端设备的第m次迭代参数，m为大于或等于1的整数；
    根据所述多个终端设备中其他终端设备的第m次迭代参数和所述第一终端设备的第m次迭代参数，确定所述第一终端设备的第(m+1)次迭代参数；
    重复上述步骤，直到所有的迭代参数不再发生变化；
    根据最后一次的迭代参数，确定所述第一终端设备的位置。
  22. 根据权利要求19-21中任一项所述的通信设备，其特征在于，所述最大似然函数中还包括所述第一终端设备的时钟偏差参数，所述处理单元用于：
    根据所述第一参数，以及所述最大似然函数，确定所述第一终端设备的时钟偏差。
  23. 根据权利要求13-22中任一项所述的通信设备，其特征在于，所述第一参数包括所述第一终端设备与所述第二终端设备之间的伪距，所述处理单元用于：
    根据所述第一终端设备与所述第二终端设备之间的伪距，确定平方距离矩阵；
    根据所述平方距离矩阵，通过多维标定算法或半正定规划算法确定所述第一终端设备的位置。
  24. 根据权利要求13-23中任一项所述的通信设备，其特征在于，所述第一终端设备的位置包括所述第一终端设备的二维位置信息和/或三维位置信息。
  25. 一种通信设备，其特征在于，所述通信设备包括处理器和存储器，所述存储器用于存储计算机程序，所述处理器用于调用并运行所述存储器中存储的计算机程序，以执行如权利要求1至12中任一项所述的方法。
  26. 一种芯片，其特征在于，所述芯片包括处理器，所述处理器用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行如权利要求1至12中任一项所述的方法。
  27. 一种计算机可读存储介质，其特征在于，用于存储计算机程序，所述计算机程序使得计算机执行如权利要求1至12中任一项所述的方法。
  28. 一种计算机程序产品，其特征在于，包括计算机程序指令，所述计算机程序指令使得计算机执行如权利要求1至12中任一项所述的方法。
  29. 一种计算机程序，其特征在于，所述计算机程序使得计算机执行如权利要求1至12中任一项所述的方法。
  30. 一种通信系统，其特征在于，包括如权利要求13至24中任意一项所述的终端设备。
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