CN113170408B

CN113170408B - Method and device for determining position

Info

Publication number: CN113170408B
Application number: CN201980081690.9A
Authority: CN
Inventors: 卢前溪; 沈渊; 刘袁鹏
Original assignee: Tsinghua University; Guangdong Oppo Mobile Telecommunications Corp Ltd
Current assignee: Tsinghua University; Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date: 2019-03-01
Filing date: 2019-03-01
Publication date: 2022-12-06
Anticipated expiration: 2039-03-01
Also published as: CN113170408A; WO2020177042A1

Abstract

The application discloses a method and equipment for determining a position, wherein the method comprises the following steps: determining the position of the first terminal equipment according to first parameters, wherein the first parameters comprise at least two of the following parameters: the pseudorange between the first terminal device and a satellite, the pseudorange between the first terminal device and a network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and a second terminal device, or the first parameter includes the pseudorange between the first terminal device and the second terminal device. The method can determine the position of the terminal equipment by combining a plurality of measurement parameters, and can improve the positioning accuracy compared with a scheme of positioning by only adopting a single measurement quantity.

Description

Method and device for determining position

Technical Field

The embodiment of the application relates to the field of communication, in particular to a method and equipment for determining a position.

Background

With the development of the technology, more and more terminal devices need to be positioned, and the requirement of a user on the positioning accuracy of the terminal devices is higher and higher.

How to realize more accurate positioning of the terminal equipment becomes a problem which needs to be solved urgently.

Disclosure of Invention

The embodiment of the application provides a method and equipment for determining a position, which can realize accurate positioning of terminal equipment.

In a first aspect, a method for determining a position is provided, including: determining the position of the first terminal equipment according to first parameters, wherein the first parameters comprise at least two of the following parameters: the pseudorange between the first terminal device and a satellite, the pseudorange between the first terminal device and a network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and a second terminal device, or the first parameter includes the pseudorange between the first terminal device and the second terminal device.

In a second aspect, a communication device is provided, which may perform the method of the first aspect or any optional implementation manner of the first aspect. In particular, the communication device may comprise functional modules for performing the method in the first aspect or any possible implementation manner of the first aspect.

In a third aspect, a communication device is provided that includes a processor and a memory. The memory is used for storing a computer program, and the processor is used for calling and running the computer program stored in the memory to execute the method of the first aspect or any possible implementation manner of the first aspect.

In a fourth aspect, a chip is provided for implementing the method of the first aspect or any possible implementation manner of the first aspect. In particular, the chip comprises a processor for calling and running a computer program from a memory, such that a device in which the chip is installed performs the method as described above in the first aspect or any possible implementation manner of the first aspect.

In a fifth aspect, a computer-readable storage medium is provided for storing a computer program, which causes a computer to perform the method of the first aspect or any possible implementation manner of the first aspect.

In a sixth aspect, there is provided a computer program product comprising computer program instructions to cause a computer to perform the method of the first aspect or any possible implementation manner of the first aspect.

In a seventh aspect, a computer program is provided, which, when run on a computer, causes the computer to perform the method of the first aspect or any possible implementation manner of the first aspect.

In an eighth aspect, a communication system is provided, comprising a communication device, wherein the communication device is configured to: determining the position of the first terminal equipment according to first parameters, wherein the first parameters comprise at least two of the following parameters: the pseudorange between the first terminal device and a satellite, the pseudorange between the first terminal device and a base station, the angle between the first terminal device and the base station, the pseudorange between the first terminal device and a second terminal device, or the first parameter includes the pseudorange between the first terminal device and the second terminal device.

According to the technical scheme, the position of the terminal equipment can be determined by combining a plurality of measurement parameters, and compared with a scheme of positioning by only adopting a single measurement quantity, the positioning accuracy can be improved. In addition, the embodiment of the application also provides a positioning scheme based on the pseudo range between the terminal devices, and the positioning of the terminal devices can be realized under the condition of no base station or satellite assistance.

Drawings

Fig. 1 is a schematic diagram of a car networking communication mode provided in an embodiment of the present application.

Fig. 2 is a schematic diagram of another internet of vehicles 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 disclosure.

Fig. 4 is a schematic flow chart of a method for determining a position according to 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 configuration diagram of another communication apparatus 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 of an embodiment of the present application.

Detailed Description

Technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The technical scheme of the embodiment of the application can be applied to various communication systems, for example: a Global System for Mobile communications (GSM) System, a Code Division Multiple Access (CDMA) System, a Wideband Code Division Multiple Access (WCDMA) System, a General Packet Radio Service (GPRS), a Long Term Evolution (Long Term Evolution, LTE) System, an LTE Frequency Division Duplex (FDD) System, an LTE Time Division Duplex (TDD), a Universal Mobile Telecommunications System (UMTS), a Worldwide Interoperability for Microwave Access (WiMAX) communication System, or a 5G System.

The network device mentioned in the embodiments of the present application may be a device that communicates with a terminal device (or referred to as a communication terminal, a terminal). A network device may provide communication coverage for a particular geographic area and may communicate with terminal devices located within that coverage area. In an embodiment, the Network device 110 may be a Base Transceiver Station (BTS) in a GSM system or a CDMA system, a Base Station (NodeB, NB) in a WCDMA system, an evolved Node B (eNB or eNodeB) in an LTE system, a Base Station (gNB) in a new wireless system, a Radio controller in a Cloud Radio Access Network (CRAN), or a Network device in a Mobile switching center, a relay Station, an Access point, a vehicle-mounted device, a wearable device, a hub, a switch, a bridge, a router, a Network-side device in a 5G Network, or a Network device in a future evolved Public Land Mobile Network (PLMN), or the like.

The terminal device mentioned in the embodiments of the present application may be any terminal device that needs to determine the location information. The terminal Equipment may refer to an access terminal, user Equipment (UE), subscriber unit, subscriber station, mobile station, remote terminal, mobile device, user terminal, wireless communication device, user agent, or User Equipment. An access terminal may be a cellular telephone, a cordless telephone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device having Wireless communication capabilities, a computing device or other processing device connected to a Wireless modem, a vehicle mounted device, a wearable device, a terminal device in a 5G network, or a terminal device in a future evolved PLMN, etc.

The terminal equipment can be a vehicle-mounted terminal in the Internet of vehicles, and the requirement on the position accuracy of the vehicle in the Internet of vehicles is very high. The vehicle needs to accurately determine the current position of the vehicle, so that unmanned driving can be better realized.

The terminal equipment needs to be positioned in various scenes so as to better realize the functions of the terminal equipment. For example, in a navigation system of a terminal device, the terminal device needs to accurately locate a current position to plan a reasonable navigation route for a user, so as to improve user experience.

The embodiment of the application can be applied to any terminal equipment-to-terminal equipment communication framework.

For example, vehicle to vehicle (V2V), vehicle to other device (V2X), device to device (D2D), and the like.

The application scenarios of the embodiment of the present application are introduced below, and mainly the car networking is taken as an example for introduction.

In one embodiment, in some embodiments of the present application, the embodiments of the present application may be applied to transmission mode 3 and transmission mode 4 defined in the third generation partnership project (3 rd generation partnership project,3 gpp) Rel-14.

Fig. 1 is a schematic view of mode 3 of the embodiment of the present application. Fig. 2 is a schematic diagram of mode 4 of the embodiment of the present application.

In transmission mode 3 shown in fig. 1, transmission resources of in-vehicle terminals (in-vehicle terminal 121 and in-vehicle terminal 122) are allocated by base station 110, and the in-vehicle terminals perform data transmission on a sidelink according to the resources allocated by base station 110. Specifically, the base station 110 may allocate resources for single transmission to the terminal, or may allocate resources for semi-static transmission to the terminal.

In the transmission mode 4 shown in fig. 2, the vehicle-mounted terminals (vehicle-mounted terminal 131 and vehicle-mounted terminal 132) adopt a transmission mode of listening (sending) and reserving (reserving), and the vehicle-mounted terminals autonomously select transmission resources on resources of the sidelink for data transmission.

In the internet of vehicles system, the vehicle needs to determine the current position in real time to avoid collision with other objects.

Currently, a common positioning method is to use a base station for positioning or a satellite for positioning.

The base station location may be based on observed time difference of arrival (OTDOA) for location. The satellite positioning may be based on a hyperbolic positioning algorithm. The two positioning methods have the same principle, and the algorithm thereof is described below by taking a satellite as an example.

In general, a satellite may send a signal to a terminal device, and the terminal device may determine a signal arrival time difference according to a reception time of the signal and a time when the satellite transmits the signal; and determining the measuring distance between the terminal equipment and the satellite according to the signal arrival time difference. When the terminal device determines the time difference of arrival of the signal, because the clock of the terminal device is not synchronous with the clock of the satellite, there is clock deviation, or in the process of signal transmission, because of the influence of factors such as signal noise, clock noise and the like, the time difference of arrival of the signal determined by the terminal device is not equal to the real signal transmission time, and thus the distance calculated by the time difference of arrival is not the real distance between the terminal device and the satellite, and we can refer to the measured distance as pseudo-range.

The position of the terminal equipment can be determined according to the pseudo range between the terminal equipment and the satellite. For example, a reference satellite may be used as a satellite, and the pseudoranges of the reference satellite may be subtracted from the pseudoranges of other satellites to obtain the difference between the pseudoranges of the two satellites. Because the difference can eliminate the influence of the clock bias of the terminal equipment, the difference of the pseudo ranges can more truly approximate the difference of the distances from the two satellites to the terminal equipment. Further, the position estimate of the vehicle may be obtained by applying a taylor algorithm of a first order approximation by performing a least squares cost function on the plurality of distance differences.

However, with the development of the 5G technology, the terminal equipment has higher and higher requirements on positioning accuracy. Especially in the car networking system, the requirement on the positioning accuracy is more strict.

The least square cost function is not accurate enough, and a first-order approximate taylor algorithm is directly adopted for positioning, which can cause that the error is easy to converge to the wrong position when the measurement error is large, so that the error between the calculated position of the terminal equipment and the actual position is large, and the positioning accuracy is not high.

In addition, due to the special high-altitude characteristic of the satellite system, the satellite system can only realize the meter-level two-dimensional plane precision, and the positioning precision in height is very poor and reaches the ten meter level. Although the positioning accuracy of the base station in height is higher than that of the satellite, the base station is easily shielded, so that the number of the base stations which can be acquired by the vehicle is limited, and the vehicle cannot be positioned by using the shielded base station; and the base station has co-channel interference, and the signal of the base station at a far distance is easily interfered by the signal of the base station at a near place, so the positioning precision of the base station is limited and is about ten meters. Conventional positioning algorithms rely on only a single satellite system or base station system, taking into account only a single measurement quantity, such as the pseudoranges of the base stations or the pseudoranges of the satellites. Because the measurement volume is less, can not exert satellite and the different advantage of basic station, can not satisfy the precision requirement of car networking sub-meter level.

In addition, the antenna array at the base station end can measure the angle, and the terminal devices can also perform mutual cooperation measurement, and the measurement items capable of improving the system precision are not added into the existing algorithm. Based on this, the embodiment of the application provides a method for determining a position, which can improve the positioning accuracy of the terminal device.

As shown in fig. 3, the method of determining a position includes step S210.

S210, determining the position of the first terminal equipment according to a first parameter, wherein the first parameter comprises 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 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 includes the pseudorange between the first terminal device and the second terminal device.

The first terminal device may be a vehicle-mounted terminal in a vehicle networking system, such as a vehicle; the first terminal device may also be a terminal device of another network, for example, a mobile terminal, and the type of the first terminal device is not specifically limited in this embodiment of the application.

The second terminal device in the embodiment of the present application may represent any other terminal device except the first terminal device.

The network device in the embodiment of the present application may be, for example, a base station. For convenience of understanding, the following description takes a network device as an example of a base station.

The first parameter is a parameter obtained by measurement, such as a pseudo-range measurement value and an angle measurement value. For some terminal devices, it may also be possible to perform angle measurement for the terminal devices, for which case the first parameter may also include angle measurement values between the terminal devices.

According to the technical scheme, the measurement quantities in the base station system, the satellite system and the terminal network system can be fused to position the terminal equipment, and compared with a single measurement quantity scheme, the positioning accuracy can be improved.

Furthermore, the first parameter may also comprise only one of the above parameters, e.g. the first parameter may comprise only a pseudorange between the terminal devices, or only an angle between the first terminal device and the base station. Through the first parameter, the position 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 longitude and latitude coordinates of the first terminal device, and the relative position may refer to a position of the first terminal device relative to other terminal devices.

The location information of the first terminal device may include three-dimensional location information or two-dimensional location information of the first terminal device, which is not limited in this embodiment.

For convenience of description, in the embodiments of the present application, a terminal device, a satellite, and a base station may be collectively referred to as a node. The pseudorange between the first terminal device and the node may be obtained using conventional methods of measuring the pseudorange.

The satellite in the embodiment of the present application may be a Global Positioning System (GPS) satellite, or a beidou satellite, and the like, which is not limited herein.

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 another system.

The angle between the first terminal device and the base station may refer to an angle between the base station and the first terminal device measured by an antenna array of the base station. The angle between the first terminal device and the base station may comprise 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 in which the position of the first terminal device is determined. It is assumed that the first parameters comprise a pseudorange between the first terminal device and the satellite and a pseudorange between the first terminal device and the base station.

As an example, the manner of determining the position may be that the position of the first terminal device is calculated according to a pseudo range between the first terminal device and the satellite and a pseudo range between the first terminal device and the base station, respectively, that is, the position X1 of the first terminal device may be calculated according to a pseudo range between the first terminal device and the satellite, then the position X2 of the first terminal device may be calculated according to a pseudo range between the first terminal device and the base station, and finally the position of the first terminal device may be determined according to the position X1 and the position X2.

Determining the location of the first terminal device according to the location X1 and the location X2 may refer to taking an average of the location X1 and the location X2 as the location of the first terminal device. Alternatively, different weights may be set for the position X1 and the position X2, respectively, to calculate the position of the first terminal device.

The embodiment of the present application does not limit a manner of calculating the position X1 of the first terminal device according to the pseudo range between the first terminal device and the satellite. For example, the position X1 of the first terminal device may be determined by using a conventional least squares cost function; alternatively, the position X1 of the first terminal can also be determined from a hyperbolic positioning algorithm.

Similarly, the manner of calculating the position X2 of the first terminal device based on the pseudorange between the first terminal device and the base station may also be any of the manners described above.

As a further example, the position may be determined by fusing the pseudo-range between the first terminal device and the satellite and the pseudo-range between the first terminal device and the base station in a cost function, and determining the position of the first terminal device by iterating the cost function.

For convenience of description, the pseudo range between the first terminal device and the satellite is simply referred to as the pseudo range of the satellite, and the pseudo range between the first terminal device and the base station is simply referred to as the pseudo range of the base station.

As mentioned above by way of example with the pseudoranges of the satellites and the pseudoranges of the base station, the first parameter of the embodiments 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 pseudoranges between the first terminal device and other terminal devices.

Of course, the first parameter may also include other measurement quantities, for example, in the case that an angle measurement can be performed between the terminal device and the terminal device, positioning may also be performed according to the angle between the terminal devices. Any parameter for which a position determination can be made may be included in the first parameter.

The embodiment of the application can also set weights for different parameters respectively. That is, each of the first parameters 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 the actual situation. According to the embodiment of the application, the position of the first terminal device can be determined according to the first parameter and the weight information of each parameter in the first parameter.

This way of determining the position may set different weights for different parameters, depending on the specific situation. For example, in the case that the measurement parameter is relatively accurate, a higher weight may be set for the parameter, and in the case that the measurement parameter error is large, a lower weight may be set for the parameter, so that when the position of the first terminal device is determined according to a plurality of parameters, the accuracy of the position of the first terminal device can be ensured.

In addition to the effects of clock skew, the skew in distance is primarily due to noise, which may include signal noise and/or clock noise. Since noise cannot be eliminated and avoided, the influence of noise can be reduced as much as possible when determining the position of the terminal device. As one implementation, different weights may be set for different parameters based on noise to improve positioning accuracy.

It is assumed that 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, and the angle between the first terminal device and the base station has a fourth weight.

Since the clock of the satellite is relatively stable, the influence of the clock noise of the satellite may not be considered, and the first weight may be determined according to the variance of the signal noise when determining the weight. There may be an influence of clock noise for the base station and the second terminal device, and therefore, the second weight and the third weight may be determined jointly from the variance of the signal noise and the variance of the clock noise. The angle measured by the base station to the first terminal device may also be affected by signal noise, and therefore the fourth weight may be determined from the covariance of the signal noise.

As one implementation, the first weight may be an inverse of a variance of the signal noise, the second weight and the third weight may be an inverse of a sum of a variance of the signal noise and a variance of the clock noise, and the fourth weight may be an inverse matrix of a signal noise covariance.

In one embodiment, the pseudorange between the first terminal device and the second terminal device may be used to determine a range estimate, which may be the mean of the pseudorange obtained by the first terminal device with the second terminal device and the pseudorange obtained by the second terminal device with the first terminal device; determining the location of a terminal device based on the first parameter may refer to determining the location of the first terminal device based on the distance estimate.

According to the method and the device, the characteristic that two-way distance measurement can be carried out between the terminal devices is utilized, when positioning is carried out, the mean value (namely the distance estimation value) of the two-way distance measurement is adopted as the first parameter to carry out calculation, and the distance estimation value can eliminate the influence of clock deviation of the terminal devices, so that the distance between the two terminal devices can be reflected more truly, and the positioning accuracy can be improved by adopting the distance estimation value to carry out positioning.

In an implementation manner, in the embodiment of the present application, an algorithm used for determining the location of the first terminal device is not limited. For example, a maximum likelihood function may be constructed based on maximum likelihood theory, from which the location of the first terminal device is determined. The maximum likelihood function will be described in detail below.

The maximum likelihood function can also comprise a clock deviation parameter, and the clock deviation of the terminal equipment can be determined while the position of the terminal equipment is determined. Specifically, the clock offset of the first terminal device may be calculated based on the first parameter and the maximum likelihood function.

The calculation of the maximum likelihood function to determine the position of the terminal device may be performed by any one of the nodes of the terminal device, the base station and the satellite.

The likelihood function may be a centralized likelihood function, which indicates that the location information of all terminal devices is obtained by iterating the likelihood function by the same computing node.

Alternatively, the likelihood function may be a distributed likelihood function, meaning that each terminal device calculates only its own location information. The positions of the plurality of terminal devices may be obtained by iterating the likelihood function by each of the plurality of terminal devices.

The first terminal device determines the position of the first terminal device according to the first parameter and the maximum likelihood function, the first terminal device can iterate the likelihood function according to the first parameter to obtain an mth iteration parameter of the first terminal device, and m is an integer greater than or equal to 1; then, determining the (m + 1) th iteration parameter of the first terminal device according to the mth iteration parameter of other terminal devices in the plurality of terminal devices and the mth iteration parameter of the first terminal device; repeating the steps until all iteration parameters are not changed or the maximum iteration times are reached; and determining the position of the first terminal equipment according to the last iteration parameter.

The maximum likelihood function provided by the embodiments of the present application is described in detail below with reference to specific examples.

We can assume that there is N in the system _c A terminal device, N _b A base station, N _s A satellite, wherein the locations of the base station and the satellite are known. The N is _c The terminal device can calculate the sum of N _b Pseudoranges between base stations, and/or N _s Pseudoranges between the satellites. The set of terminals, base stations and satellites are defined as follows:

and

the terminal device may be a vehicle, N _c The terminal equipment can refer to N in the vehicle networking system _c And (4) a vehicle.

The position of node k (including terminal equipment, base stations and satellites) is denoted as p _k ＝[x _k ，y _k ，z _k ] ^T The parameter vector containing the positions of all the terminal devices is recorded as

We can define the measurement form and estimation form of the parameter a as

And

the embodiments of the present application may assume that the satellite and the base station are synchronized, that is, there is no clock skew between the satellite and the base station. The terminal device k has clock deviation delta from the base station and the satellite due to the limitation of hardware equipment _k 。

Defining the distance d of node k from observation node j _kj Angle of pitch theta _kj And azimuth angle phi _kj Respectively as follows:

d _kj ＝||p _k -p _j ||

wherein p is _k Indicating the position of the node, p _j Indicating the location of node j.

Node k may receive a signal from node j, which may be, for example, a first terminal device, and node j may be any one of a satellite, a base station, and other terminal devices.

Node k may receive a signal from node j, which may be written as follows:

r _kj (t)＝α _kj S _j (t-τ _kj )+n _kj (t) (2)

wherein s is _j (t) is the known signal, its Fourier transform being s _j (f)，α _kj And τ _kj Signal amplitude and delay, n, of the transmission link from node j to node k, respectively _kj (t) is the power spectral density N ₀ White Gaussian noise of/2. That is, the signal received by node k is other than s sent by node j _j In addition to the (t) signal, a noise signal n may be included _kj (t)。

Assuming that the node j is a satellite, for the node k receiving a signal from the satellite j, the following pseudo-range model, pseudo-range measurement value

The modeling is as follows:

wherein the content of the first and second substances,

represents the pseudo-range between node k and node j, d _kj Represents the actual distance between node k and node j, b _k Representing the distance deviation, ω, introduced by the clock deviation of node k _kj Is due to signal noise n _kj (t) an equivalent zero mean Gaussian error introduced, in other words, ω _kj Is due to signal noise n _kj (t) introduced distance error.

Wherein, b _k ＝c*δ _k C is the speed of light, delta _k Which represents the clock skew of node k (or terminal device k).

ω _kj Variance of (2)

Satisfies the following conditions:

the embodiment of the application can be based on omega _kj May be used to determine the weight of the pseudorange between node k and node j. For example, the variance can be

The reciprocal of (a) is determined as the weight of the pseudorange between node k and node j.

As can be seen from the above equation, 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.

Assuming that the node j is a base station or other terminal equipment, for the node k receiving the signal from the node j, we also consider the influence of clock noise caused by clock drift of the terminal equipment and the base station, etc. Thus, the following pseudorange model may be established:

wherein, b _j Represents the clock offset induced distance deviation, v, of node j _kj Representing the range error introduced by clock noise. Variance of clock noise without calibration

Will grow over time. Variance of the clock noise

May be obtained in the factory parameters of the clock.

For the case where node j is the base station, we can assume that the base station is synchronized with the satellite and there is no clock offset, and then b is the time when node j is the base station _j And =0. At this time, the pseudo-range model may be expressed as:

for different pseudorange measurements, we introduce a parameter λ _kj It represents the inverse of the variance after superposition of two types of noise:

for the case where node j is a satellite:

for the case where node j is a base station or other terminal device:

besides the above pseudorange measurement, the embodiment of the present application also considers the property that the base station can measure the angle, and the base station j can measure the pitch angle θ between the base station j and the terminal device k _jk And azimuth angle phi _jk Its modeling may be as follows:

wherein, the first and the second end of the pipe are connected with each other,

representing a measure of pitch angle between node j and node k,

a measurement value, θ, representing the azimuth angle between node j and node k _jk Representing the actual pitch angle, phi, between node j and node k _jk Represents the actual azimuth angle, μ, between node j and node k _jk The covariance matrix can be c _jk To indicate.

c _jk Is related to the spatial structure of the base station antenna array, which may be, for exampleA rectangular array or a circular array, etc. For different spatial configurations, c _jk The expression forms of (a) and (b) are different. In the following, the antenna array of the base station is described as an example of a rectangular array, and as shown in fig. 4, the antenna array of the base station is assumed to be an M × N rectangular array.

When the antenna array shown in FIG. 4 is used for angle measurement, the antenna array can be used for angle measurement

Δ is the spacing of the elements in the diagram, or Δ can be understood as the row spacing or column spacing, and λ is the signal wavelength, then μ _jk Covariance matrix C of _jk Can be expressed as:

wherein:

a＝cos ² θ _jk (mcos ² φ _jk +nsin ² φ _jk +2lcosφ _jk sinφ _jk )

b＝cosθ _jk sinθ _jk ((n-m)cosφ _jk sinφ _jk +l(cos ² φ _jk -sin ² φ _kj ))

d＝sin ² θ _jk (msin ² φ _jk +ncos ² φ _jk -2lcosφ _jk sinφ _jk )

after the pseudo-range model and the angle model are established, the position information of the terminal equipment can be obtained through a proper algorithm.

The position of the terminal device may be calculated by conventional algorithms, for example. For another example, the position of the terminal device may be calculated based on the maximum likelihood function provided in the embodiments of the present application.

Based on maximum likelihood theory, we can construct a total likelihood function where z is a vector of all measurement components. p denotes a vector of positions of all terminal devices, and b denotes a vector of clock offsets of all terminal devices.

Wherein p is _k Indicating the location of node k, which may be a terminal device, p _j Represents the position of a node j, which may be any one of a terminal device, a base station, and a satellite, | | p _k -p _j And | represents the actual distance between node k and node j.

The above equation represents the maximum likelihood of the pseudoranges of the base station or the satellite.

The above equation represents the maximum likelihood of pseudoranges between terminal devices.

The above equation represents the maximum likelihood of the angle between the base station and the terminal device.

In the embodiment of the application, when the position of the terminal device is determined, a plurality of measurement items are considered, the plurality of measurement items can be integrated in one cost function, the cost function is iterated for a plurality of times until the cost function converges or the maximum iteration number is reached, and then the last iteration parameter can be determined as the position of the terminal device.

Secondly, the likelihood function provided by the embodiment of the application also considers the influence of clock deviation, introduces the distance deviation generated by the clock deviation into the likelihood function for calculation, and can obtain the clock deviation of the terminal equipment while calculating the position of the terminal equipment. The clock skew can play an important role in the subsequent communication process of the terminal equipment, for example, the terminal equipment can tell the clock skew of the terminal equipment to the opposite terminal equipment, so that the subsequent communication is facilitated.

Of course, the likelihood function according to the embodiment of the present application is not limited to the above form, and for example, the position estimation may be performed directly by the measured pseudorange without considering the range bias due to the clock bias.

Further, the embodiment of the present application also considers the characteristic that bidirectional ranging can be performed between terminal devices, that is, the first parameter may include a pseudorange obtained by the first terminal device with the second terminal device, and a pseudorange obtained by the second terminal device with the first terminal device. Therefore, the measured bidirectional pseudo-range between the first terminal device and the second terminal device is considered and integrated into the likelihood function, and the positioning accuracy can be further improved.

The pseudo range obtained by the first terminal device k and obtained by the second terminal device j may refer to that the second terminal device j may send a first signal to the first terminal device, where the first signal may include a sending time t1 when the second terminal device j sends the first signal, and after receiving the first signal, the first terminal device k may determine, according to a receiving time t2 of the first terminal device k, that the pseudo range between the first terminal device k and the second terminal device j is

The pseudo range obtained by the second terminal device j and 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, where the second signal may include a sending time t3 when the first terminal device k sends the second signal, and after the second terminal device j receives the second signal, the pseudo range between the second terminal device j and the first terminal device k may be determined to be the pseudo range between the second terminal device k and the first terminal device k according to a receiving time t4 of the second terminal device j

At this time, the maximum likelihood of the pseudo range between the terminal devices in the maximum likelihood function may be modified to be:

representing the maximum likelihood of the pseudorange obtained by node k with node j,

representing the maximum likelihood of the pseudorange obtained by node j with node k.

Further, the embodiments of the present application may also set different weights for different parameters, and for the pseudorange of the satellite, we may only consider the influence of the signal noise, so that the weight may be set for the pseudorange of the satellite based on the signal noise, for example, the inverse λ of the variance of the signal noise _kj The weights for the pseudoranges to the satellites are set,

node j represents a satellite.

For the pseudorange of the base station, we can consider the influence of both signal noise and clock noise, and the pseudorange of the base station can be determined according to the variance of the signal noise and the variance of the clock noise, for example, the weight of the pseudorange of the base station can be the reciprocal of the sum of the variance of the signal noise and the variance of the clock noise,

node j represents a base station.

For the terminal equipmentSimilar to the pseudorange of the base station, we can set a weight for the pseudorange between the terminal devices, taking into account the effects of both signal noise and clock noise, for example

Node j represents the other terminal device.

For the angle measurement of the base station, the embodiment of the application can consider the influence of equivalent zero mean gaussian noise on a two-dimensional angle introduced by signal noise, and the covariance matrix of the signal noise can be used for determining the weight of the angle measurement. For example, the inverse of the covariance matrix is determined as the weight of the angle measurement.

We can add the above weight information to the maximum likelihood function to determine the location of the terminal device.

The maximum likelihood function can be deformed as:

in the above likelihood function, different weights λ may be set for different parameters _kj 。

Since the variance of the noise is inversely proportional to the signal-to-noise ratio, and λ _kj Inversely proportional to the variance of the noise, and thus, λ _kj Proportional to the signal-to-noise ratio, i.e. the greater the signal-to-noise ratio, the weight λ _kj The larger. If the signal-to-noise ratio of a measurement quantity is relatively large, which indicates that the noise in the signal is relatively small, a relatively large weight can be given to the measurement quantity; a measurement may be given less weight if its signal-to-noise ratio is smaller, indicating a greater noise ratio in the signal. The method for setting the weight is reasonable, the influence of signal noise and clock noise is considered in the algorithm, the position of the terminal equipment determined by the maximum likelihood function is closer to the actual position, and the positioning accuracy is higher.

For the maximum likelihood function, the manner used for solving the maximum likelihood function is not specifically limited in the embodiment of the present application. For example, it may be a gradient descent method, an EM algorithm, a coordinate ascent or descent algorithm, or the like. The following describes the solving process of the likelihood function by taking the gradient descent algorithm as an example.

For the above-mentioned likelihood functions, our aim is to find the appropriate P and b such that the above-mentioned likelihood function values are maximized. Because the likelihood function is in exponential form, we only need to get the maximum of the exponential term to get the maximum of the likelihood function. That is, the following cost function H (p, b) value is minimized.

H (p, b) is expressed in the form of a weighted sum of squares. Two parts are included, one is information from the anchor point, such as pseudorange and angle information from the base station, and pseudorange information from the satellite. The other part is pseudo range information from other terminal devices. Wherein the content of the first and second substances,

are the measured pseudorange values and angle values. Our goal is to minimize the deviation between the resolved pseudorange and angle values and the measured pseudorange and angle values.

For the above likelihood function, since it includes all the measurement information, that is, N _c Terminal device, N _b A base station and N _s Measurement information between all nodes between satellites, so we can refer to this likelihood function as a centralized positioning algorithm.

When a gradient descent algorithm is used for solving, we can give the gradient (i.e., the first derivative) of each polynomial in H (P, b) for P and b. For each polynomial in H (p, b), it represents only the measurement between node j and node k, and therefore only the unknown parameter p of the terminal device _j ，p _k ，b _j ，b _k It is related.

For pseudorange measurements, we take the case of pseudorange measurements between terminal devices, either base stations or satellitesTo position parameter p of terminal equipment _k And a clock deviation parameter b _k The first derivative of (A) can also be obtained by analogy with the following formula, i.e. only p in the polynomial _j ，b _j As known parameters of the corresponding satellite or base station.

For the measurement item of the pseudo range between the terminal devices, we derive it, and can obtain:

for angle measurement between a base station and a terminal device, first defined are:

the gradient corresponding to the angle measure is:

after the first derivatives of the polynomials are obtained, the likelihood function may be iterated a first time to obtain the minimum of the first iteration. And further, performing second iteration according to the iteration parameters of the first iteration to obtain the iteration parameters of the second iteration. And sequentially circulating until the iteration parameters are not changed any more or the maximum iteration times are reached.

In solving the likelihood function, pseudoranges and angle measurements between the terminal device and all nodes may be input. The initial state of all terminal devices can then be specified

And

and iterates according to the initial state. For the mth iteration parameter

And

can be based on the overall cost function and the current iteration parameters

And

calculating the gradient of the position and clock parameters according to the gradient expression given above, and updating the parameters of the next round according to the gradient decrease

And

m is an integer of 1 or more. Until the likelihood function converges or a maximum number of iterations is reached; and determining the position and the clock deviation of the terminal equipment according to the iteration parameters corresponding to the last iteration.

In addition to the above-described manner of determining the weight, other manners of determining the weight may be possible. As an implementation, fixed weight information may be set for each measurement quantity, for example, the weights of the pseudo range of the satellite, the pseudo range of the base station, the angle of the base station, and the pseudo range between the terminal devices may be 0.3, 0.2, and 0.2, respectively.

The above calculation process is described assuming that all the measurement items exist. Of course, only some of the measurement items may be present, and for the case of only some measurement items, the likelihood function and the calculation process thereof are also applicable, and only the measurement items missing in the measurement need to be set to 0.

In the case where there is no measurement item of the base station or satellite system, that is, there is no base station or satellite-assisted positioning, and the first parameter value only includes the pseudorange of the terminal device, if the above-mentioned given gradient descent algorithm is directly used for positioning, if the given initial value is not good enough, it is easy to cause a situation that the terminal device does not converge or converges to an incorrect position, that is, the calculated position of the terminal device is greatly different from the actual position.

Because of no satellite and base station assistance, the first vehicle can be taken as a clock reference at the moment, and the distance deviation b caused by the clock deviation can be enabled to be ₁ =0, then the distance estimate between the terminal devices and the clock skew of the other vehicle relative to the first vehicle can be derived from the two-way measurement.

Since the formula (5) relates to the distance d _kj And deviation b _k ，b _j So that all distances d can be obtained by directly using the least squares _kj And a distance deviation b _k Is estimated.

The embodiment of the present application further provides another simple way to obtain distance estimation, that is, directly averaging two-way ranging to obtain a distance estimation value:

and the distance estimation value is adopted for positioning, so that the influence of clock deviation of the first terminal equipment and the second terminal equipment on the distance estimation can be eliminated.

After obtaining the estimated values of the distances between all the nodes, the shape of the terminal equipment network can be obtained directly through a classical multidimensional calibration algorithm, or through other algorithms such as a semi-positive definite programming algorithmA "shape estimate" of the network of terminal devices is obtained. The following multi-dimensional calibration algorithm is used as an example to illustrate, and the square distance matrix

Can be expressed as:

for square distance matrix

Without measured distance values, a classical shortest path algorithm may be used instead. Then the distance matrix of the square

The shape of the terminal equipment network can be obtained by adopting a multidimensional calibration algorithm.

The multidimensional calibration algorithm can be implemented as follows:

first, the squared distance matrix

And removing the centroid to obtain a G matrix.

Wherein L = I-1/N _c 11 ^T I is N _c Dimensional unit array, 1 being N _c A column vector with dimension all 1. And decomposing the eigenvalue of the G matrix to obtain an eigenvalue and a corresponding eigenvector thereof. And taking out the maximum three eigenvalues and the corresponding eigenvectors to multiply respectively to obtain three weighted vectors, and arranging the three vectors according to the order of the eigenvalues from big to small to obtain a three-column matrix, namely the three-dimensional position parameter matrix. If only a two-dimensional position matrix is required, only the first two columns of the three-column matrix are taken.

The centralized positioning algorithm described above requires that all measurements in the network be aggregated and that all these measurements need to be at one central pointThe centralized calculation, i.e. the position of all terminal devices and the clock offset, is calculated from a central point. The central point may be any one of a terminal device, a base station, and a satellite. The algorithm is directly corresponding to N _c The calculation of p and b of each vehicle is carried out, the calculation space is large, the complexity is high, and the calculation capacity of the central point is also high.

In addition, in a mobile network, in order to maintain real-time performance, all data cannot be collected to a central node for calculation in many cases, and most of the calculation capacity of the nodes cannot calculate parameters of all nodes in real time.

Based on this, the embodiments of the present application provide a distributed positioning algorithm, which can decompose the calculation process, and each terminal device k only needs to calculate its own position p _k And clock deviation b _k In this way, the positions and clock offsets of all terminal devices can also be obtained. The calculation mode can reduce the calculation complexity of the calculation node, improve the calculation rate and ensure the real-time requirement in the mobile network.

For the distributed positioning algorithm, terms related to the terminal equipment k can be extracted from the centralized cost function H (p, b) to construct a local cost function H _k (p _k ，b _k ) The following are:

each terminal device may iterate the likelihood function in the derivation manner described above, and each terminal device iterates its respective likelihood function to find its corresponding position and clock offset.

The specific iterative process is as follows:

the first terminal device may iterate the distributed likelihood function according to the first parameter to obtain an mth iteration parameter of the first terminal device, where m is an integer greater than or equal to 1.

The first terminal device may receive the mth iteration parameter of the other terminal device broadcasted by the other terminal device, and obtain the (m + 1) th iteration parameter of the node by using a gradient descent algorithm according to the mth iteration parameter of the other terminal device.

And repeating the steps until all iteration parameters are not changed or the maximum iteration times are reached.

And the first terminal equipment determines the position and the clock offset of the first terminal equipment according to the last iteration parameter. 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.

Likewise, the second terminal device may adopt the above steps to obtain the position and clock offset of the second terminal device. By analogy, each terminal device can obtain the position and the clock offset of the node. Thus, the position and clock offset of the whole terminal equipment system can be obtained.

For the local positioning algorithm, when there is no anchor point, that is, there is no base station system and satellite system for assisting positioning, the gradient descent algorithm described above can be directly used for calculation. However, if the initial value given is not good enough, it is likely that the convergence is not achieved or the convergence is not at the wrong position.

Based on this, the embodiment of the present application provides a calculation method, which can avoid the situation of non-convergence or convergence to an error position. This calculation is described below.

Each terminal device can obtain its distance value from the neighbor by equation (6), and each terminal device can broadcast all the distance values it obtains to other terminal devices. In this way, each terminal device can obtain all the 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 itself. The terminal device may obtain the "shape" of the 1-hop network of each terminal device according to the distance measurement values (or referred to as pseudoranges) of all nodes within the 1-hop range and according to a multidimensional calibration algorithm or a semi-positive planning algorithm. Further, these local structures can be fused together to get the "shape" of the entire network. The specific calculation process is as follows:

the input is the pseudoranges 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 local 1-hop network 'shape' of own 0 th iteration by using the multi-dimensional calibration algorithm described above "

And broadcasts it to the neighbors.

Starting from any terminal device, it is defined as the originating network, and here, the terminal device k is defined as the originating network as an example.

For the mth iteration parameter

The terminal device k may never be present

Selects the terminal device j so that

To know

At most, m is an integer of 1 or more.

Spatial relationships through common nodes will

And

are fused into a compound containing

And

the new network 'shape' of all the nodes updates the converged network into

Up to

All terminal devices are included. When in use

When all the terminal devices are included, they are defined as the overall "shape" of the network.

Compared with the 3GPP positioning algorithm which only contains pseudo-range measurement parameters and only uses single kind of information (such as a base station or a satellite), the embodiment of the application not only adds the angle measurement of the base station and the pseudo-range measurement of mutual cooperation between terminal devices, but also integrates all the measurements into one cost function in the algorithm, and positioning is carried out through the fused cost function, so that the positioning precision can be improved.

The maximum likelihood function provided by the embodiment of the application has inclusiveness, and for unknown measurement items or measurement items which are not carried out, only the part lacking in measurement needs to be set to be 0, and the likelihood function can still be used for positioning. For example, in the case of only the angle measurement and the pseudo range measurement of the base station, only the polynomial concerning the pseudo range of the satellite and the polynomial concerning the pseudo range between the terminal devices need to be set to 0, and only the polynomial concerning the angle of the base station and the pseudo range need to be iterated to obtain the position information of the terminal device.

The maximum likelihood function provided by the embodiment of the application can realize the positioning of the terminal equipment and the estimation of the clock offset of the terminal equipment.

In addition, the gradient descent algorithm is adopted to solve the maximum likelihood function, and only the gradient needs to be calculated in the iteration process due to the use of the gradient descent algorithm. And the gradient part has a closed expression, so that the complexity is low. Especially for a network with high real-time requirement, such as an internet of vehicles, the low complexity can meet the real-time requirement. The distributed positioning algorithm provided by the embodiment of the application can further reduce the calculation complexity and improve the real-time performance.

The method for determining the position provided by the embodiment of the present application is described above in detail, and the apparatus of the embodiment of the present application is described in detail below with reference to fig. 5 to 8, and the apparatus embodiment and the method embodiment correspond to each other, so that the parts not described in detail can be referred to the previous method embodiments.

Fig. 5 is a schematic block diagram of a communication device 500 provided in an embodiment of the present application. The communication device 500 shown in fig. 5 may be a transmitting end device in a method embodiment. The communication device may include a processing unit 510.

A processing unit 510, configured to determine a location 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 a satellite, the pseudorange between the first terminal device and a network device, the angle between the first terminal device and the network device, the pseudorange between the first terminal device and a second terminal device, or the first parameter includes the pseudorange between the first terminal device and the second terminal device.

In an embodiment, each of the first parameters has respective weight information, and the processing unit 510 is configured to: and determining the position of the first terminal equipment according to the first parameters and the weight information of each parameter in the first parameters.

In an embodiment, 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 pseudorange between the first terminal 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 a variance of signal noise, the second weight and the third weight are determined according to a variance of signal noise and a variance of clock noise, and the fourth weight is determined according to a covariance of signal noise.

In an embodiment, the angle between the first terminal device and the network device comprises an azimuth angle and/or a pitch angle.

In one embodiment, the pseudo range between the first terminal device and the second terminal device is used to determine a distance estimation value, where the distance estimation value is an average of the pseudo range between the first terminal device and the second terminal device and the pseudo range between the second terminal device and the first terminal device; the processing unit 510 is configured to: and determining the position of the first terminal equipment according to the distance estimation value.

In an embodiment, the processing unit 510 is configured to: and determining the position of the first terminal equipment according to the first parameter and the maximum likelihood function.

In an embodiment, the communication device is configured to obtain locations of a plurality of terminal devices, where the plurality of terminal devices includes the first terminal device, and the processing unit 510 is configured to: according to the first parameter, carrying out multiple iterations on the maximum likelihood function by adopting a gradient descent algorithm to obtain the minimum value of the maximum likelihood function; and determining the positions of the plurality of terminal devices according to the iteration parameters at the minimum value of the maximum likelihood function.

In an embodiment, the positions of the plurality of terminal devices are obtained by iterating the maximum likelihood function by the same computing node.

In an embodiment, the positions of the plurality of terminal devices are obtained by iterating the maximum likelihood function by each of the plurality of terminal devices, and the processing unit 510 is configured to: according to the first parameter, iterating the maximum likelihood function to obtain an m-th iteration parameter of the first terminal equipment, wherein m is an integer larger than or equal to 1; determining an (m + 1) th iteration parameter of the first terminal device according to the mth iteration parameter of other terminal devices in the plurality of terminal devices and the mth iteration parameter of the first terminal device; repeating the steps until all the iteration parameters are not changed any more; and determining the position of the first terminal equipment according to the last iteration parameter.

In an embodiment, the maximum likelihood function further includes a clock bias parameter of the first terminal device, and the processing unit 510 is configured to: and determining the clock deviation of the first terminal equipment according to the first parameter and the maximum likelihood function.

In an embodiment, the first parameter comprises a pseudo-range between the first terminal device and the second terminal device, and the processing unit 510 is configured to: determining a square distance matrix according to the pseudo range between the first terminal device and the second terminal device; and determining the position of the first terminal equipment by a multi-dimensional calibration algorithm or a semi-positive planning algorithm according to the square distance matrix.

In an embodiment, the location of the first terminal device comprises two-dimensional location information and/or three-dimensional location information of the first terminal device.

It should be understood that the communication device 500 may perform the corresponding operations performed by the communication device in the above-described method, and therefore, for brevity, the description is not repeated herein. The communication device 500 may be, for example, a terminal device, a network device, or a satellite as described above.

Fig. 6 is a schematic structural diagram of a communication device 600 according to 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 a memory to implement the method in the embodiment of the present application.

In an embodiment, as shown in fig. 6, the communication device 600 may further include a memory 620. From the memory 620, the processor 610 may call and run a computer program to implement the method in the embodiment of the present application.

The memory 620 may be a separate device from the processor 610, or may be integrated into the processor 610.

In one embodiment, as shown in fig. 6, the communication device 600 may further include a transceiver 630, and the processor 610 may control the transceiver 630 to communicate with other devices, and in particular, may transmit information or data to the other devices or receive information or data transmitted by the other devices.

The transceiver 630 may include a transmitter and a receiver, among others. The transceiver 630 may further include antennas, and the number of antennas may be one or more.

In an implementation manner, the communication device 600 may specifically be a terminal device in the embodiment of the present application, and the communication device 600 may implement a corresponding process implemented by the communication device in each method in the embodiment of the present application, and for brevity, no further description is given 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 a memory to implement the method in the embodiment of the present application.

In an embodiment, as shown in fig. 7, chip 700 may further include a memory 720. From the memory 720, the processor 710 can call and run a computer program to implement the method in the embodiment of the present application.

The memory 720 may be a separate device from the processor 710 or may be integrated into the processor 710.

In an embodiment, 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 in particular, may obtain information or data transmitted by other devices or chips.

In an embodiment, the chip 700 may further include an output interface 740. The processor 710 may control the output interface 740 to communicate with other devices or chips, and in particular, may output information or data to the other devices or chips.

In an embodiment, the chip may be applied to the terminal device in the embodiment of the present application, and the chip may implement a corresponding process implemented by the terminal device in each method in the embodiment of the present application, and for brevity, no further description is given here.

It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.

It should be understood that the processor of the embodiments of the present application may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double Data Rate Synchronous Dynamic random access memory (DDR SDRAM), enhanced Synchronous SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

It should be understood that the above memories are exemplary but not limiting illustrations, for example, the memories in the embodiments 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 SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), direct Rambus RAM (DR RAM), and the like. That is, the memory in the embodiments of the present application is intended to comprise, without being 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.

In an embodiment, the network device 810 may be configured to implement corresponding functions implemented by the network device in the above-described method, and the composition of the network device 810 may be as shown in the communication device 500 in fig. 5, which is not described herein again for brevity.

In an embodiment, the terminal device 820 may be configured to implement corresponding functions implemented by the terminal device in the foregoing method, and the composition of the terminal device 820 may be as shown in the communication device 500 in fig. 5, which is not described herein again for brevity.

The embodiment of the application also provides a computer readable storage medium for storing the computer program. Optionally, the computer-readable storage medium may be applied to the network device in the embodiment of the present application, and the computer program enables the computer to execute the corresponding process implemented by the network device in each method in the embodiment of the present application, which is not described herein again for brevity. In an embodiment, the computer-readable storage medium may be applied to a terminal device in the embodiment of the present application, and the computer program enables a computer to execute a corresponding process implemented by the terminal device in each method in the embodiment of the present application, which is not described herein again for brevity.

Embodiments of the present application also provide a computer program product comprising computer program instructions. Optionally, the computer program product may be applied to the network device in the embodiment of the present application, and the computer program instructions enable the computer to execute corresponding processes implemented by the network device in the methods in the embodiment of the present application, which are not described herein again for brevity. In an embodiment, the computer program product may be applied to a terminal device in this embodiment, and the computer program instructions enable a computer to execute corresponding processes implemented by the terminal device in the methods in this embodiment, which are not described herein again for brevity.

The embodiment of the application also provides a computer program. Optionally, the computer program may be applied to the network device in the embodiment of the present application, and when the computer program runs on a computer, the computer is enabled to execute a corresponding process implemented by the network device in each method in the embodiment of the present application, and for brevity, details are not described here again. In an embodiment, the computer program may be applied to the terminal device in the embodiment of the present application, and when the computer program runs on a computer, the computer is enabled to execute corresponding processes implemented by the terminal device in the methods in the embodiment of the present application, and for brevity, details are not described here again.

It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

It should also be understood that in the present embodiment, "B corresponding to" means that B is associated with a, from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the unit is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for determining a location, wherein the method is used to obtain locations of a plurality of terminal devices, the plurality of terminal devices including a first terminal device, and the locations of the plurality of terminal devices are obtained by iterating a maximum likelihood function for each of the plurality of terminal devices, respectively, and the method includes:

according to the first parameter, carrying out multiple iterations on the maximum likelihood function to obtain an mth iteration parameter of the first terminal equipment, wherein m is an integer greater than or equal to 1;

determining an (m + 1) th iteration parameter of the first terminal device according to the mth iteration parameter of other terminal devices in the plurality of terminal devices and the mth iteration parameter of the first terminal device;

repeating the steps until all the iteration parameters are not changed any more;

determining the position of the first terminal device according to the last iteration parameter,

wherein the first parameter comprises: a pseudorange between the first terminal device and a satellite, a pseudorange between the first terminal device and a network device, an angle between the first terminal device and the network device, and a pseudorange between the first terminal device and a second terminal device; each of the first parameters has respective weight information;

wherein a pseudorange between the first terminal device and the satellite has a first weight, a pseudorange between the first terminal device and the network device has a second weight, a pseudorange between the first terminal device and the second terminal device has a third weight, an angle between the first terminal device and the network device has a fourth weight, the first weight is determined from a variance of signal noise, the second weight and the third weight are determined from a variance of signal noise and a variance of clock noise, the fourth weight is determined from a covariance of signal noise,

wherein the maximum likelihood function integrates each of the first parameters and respective weight information for each parameter.

2. The method of claim 1, wherein the angle between the first terminal device and the network device comprises an azimuth angle and/or a pitch angle.

3. The method according to claim 1 or 2, wherein the maximum likelihood function further comprises a clock bias parameter of the first terminal device, the method further comprising:

and determining the clock deviation of the first terminal equipment according to the first parameter and the maximum likelihood function.

4. The method according to claim 1 or 2, characterized in that the location of the first terminal device comprises two-dimensional location information and/or three-dimensional location information of the first terminal device.

5. A communication device, configured to obtain locations of a plurality of terminal devices, where the plurality of terminal devices include a first terminal device, and the locations of the plurality of terminal devices are obtained by iterating a maximum likelihood function for each of the plurality of terminal devices, respectively, and the communication device includes:

a processing unit for performing the steps of:

6. The communication device according to claim 5, wherein the angle between the first terminal device and the network device comprises an azimuth angle and/or a pitch angle.

7. The communication device according to claim 5 or 6, wherein the maximum likelihood function further comprises a clock bias parameter of the first terminal device, and the processing unit is configured to:

8. The communication device according to claim 5 or 6, wherein the location of the first terminal device comprises two-dimensional location information and/or three-dimensional location information of the first terminal device.

9. A communication device, characterized in that the communication device comprises a processor and a memory for storing a computer program, the processor being adapted to invoke and execute the computer program stored in the memory to perform the method according to any of claims 1 to 4.

10. A chip, characterized in that it comprises a processor for calling up and running a computer program from a memory, causing a device in which the chip is installed to perform the method according to any one of claims 1 to 4.

11. A computer-readable storage medium for storing a computer program which causes a computer to perform the method of any one of claims 1 to 4.

12. A communication system comprising a communication device according to any of claims 5 to 8.