CN110225449B - Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method - Google Patents
Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method Download PDFInfo
- Publication number
- CN110225449B CN110225449B CN201910427793.8A CN201910427793A CN110225449B CN 110225449 B CN110225449 B CN 110225449B CN 201910427793 A CN201910427793 A CN 201910427793A CN 110225449 B CN110225449 B CN 110225449B
- Authority
- CN
- China
- Prior art keywords
- user
- rrh
- path
- measurement
- environment mapping
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000013507 mapping Methods 0.000 title claims abstract description 36
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000005259 measurement Methods 0.000 claims abstract description 54
- 238000012545 processing Methods 0.000 claims abstract description 10
- 239000013598 vector Substances 0.000 claims description 20
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 2
- 238000004891 communication Methods 0.000 description 12
- 230000005540 biological transmission Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 238000000280 densification Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000007943 implant Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Images
Classifications
-
- 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
- G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
- G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
-
- 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
- G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
- G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
- G01S11/04—Systems for determining distance or velocity not using reflection or reradiation using radio waves using angle measurements
-
- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0257—Hybrid positioning
-
- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/04—Position of source determined by a plurality of spaced direction-finders
-
- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
- H04W4/027—Services making use of location information using location based information parameters using movement velocity, acceleration information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method, which comprises the following steps: each user sends an uplink orthogonal pilot signal to each radio frequency far end, the radio frequency far end transmits the received signal to the central processing unit through a forward link, and the central processing unit acquires the measurement information of each propagation path between each radio frequency far end and each user through the received signal; the central processing unit screens out direct paths between the user and the radio frequency remote ends by using the measurement information of each path, and establishes a joint position and speed estimation model according to the measurement information of the related direct paths; designing a joint estimation algorithm according to the model to obtain the position and the speed of the user; the central processing unit screens out single-hop non-direct paths between the user and all radio frequency remote ends by using the measurement information of each path, and establishes an environment mapping model by combining the estimated user position; and designing an estimation algorithm according to the model to complete environment mapping. The invention realizes high-precision positioning with low expenditure and algorithm complexity.
Description
Technical Field
The invention relates to a 3D positioning, speed measuring and environment mapping method based on millimeter waves CRAN, and belongs to the cross field of millimeter wave communication and positioning technologies.
Background
Millimeter wave communication is considered one of the most promising technologies for 5G and future wireless communication. More accurate Time Delay (TD), time difference of arrival (TDoA) and frequency difference of arrival (FDoA) may be obtained since the millimeter wave band may provide more available spectrum and larger bandwidth than the currently used band below 6 GHz. Path loss of the millimeter wave band is large, and therefore, a difference in received power between a direct path (LoS) and a non-direct path (NLoS) is large, which makes it easier to eliminate NLoS path interference. Millimeter-wave communications require compensation for severe path loss using large-scale antenna arrays, which help achieve more accurate angle of arrival (AoA) and angle of departure (AoD), and highly directional transmission. In addition, Cloud Radio Access Networks (CRANs) may also enhance millimeter wave communication performance by improving network coverage. Therefore, the millimeter wave CRAN can realize more accurate positioning, and in turn, the position information can assist the communication system to further reduce communication delay and improve the expansibility and robustness of a future network.
CRANs provide a cost-effective way to achieve network densification, where distributed low-complexity radio remote ends (RRHs) are deployed near users and coordinated by central processing units (CUs) for joint processing. CUs have more powerful processing power than users and can therefore implement upstream multipoint positioning. Currently, researchers have proposed solutions for multi-point positioning. For example, fixed target positioning in radar systems, 3D position velocity step estimation in radar systems, 2D position estimation in CRAN systems. However, in such methods, the communication system has not been combined with the positioning function, nor has the joint 3D position velocity estimation and environment mapping been solved.
In summary, how to combine positioning into a communication system and design a joint position and velocity estimation and environment mapping algorithm with less overhead becomes one of the challenges to be overcome in the millimeter wave massive MIMO system.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for 3D positioning, velocity measurement and environment mapping based on millimeter waves CRAN, so as to obtain the position and velocity of a user in a three-dimensional space and information of an information transmission environment at the same time.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides a millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method, which comprises the following steps:
step 1, each user sends an uplink orthogonal pilot signal to each radio frequency remote RRH, the RRH transmits the received signal to a central processing unit CU through a forward link, and the CU acquires the measurement information of each propagation path between each RRH and each user through the received signal;
and 5, solving the environment mapping model established in the step 4 to complete environment mapping.
As a further technical solution of the present invention, in step 1, the measurement information of each propagation path between each RRH and each user, which is obtained by the CU, includes: the arrival angle AoA of the user uplink orthogonal pilot signal arriving at the RRH end, the time difference TDoA of the same user signal arriving at different RRHs and the frequency difference FDoA of the same user signal arriving at different RRHs.
As a further technical solution of the present invention, in steps 2 and 4, there are two methods for the CU to screen out the LoS path between the user and a plurality of RRHs and the CU to screen out the single-hop NLoS path between the user and all RRHs: (1) a CU sets a threshold value by utilizing the power estimation function of the RRH, the power exceeding the threshold value is judged as a LoS path, and the power lower than the threshold value is judged as a single-hop NLoS path; (2) and the CU classifies the LoS path and the single-hop NLoS path by utilizing the neural network through supervised learning, and trains the neural network by taking the measurement information as input.
As a further technical scheme of the invention, the joint position and velocity estimation model established in the step 2 is as follows:
h＝Gw+e
wherein, w is a six-dimensional column vector, the front three-dimensional represents the three-dimensional position coordinate of the user, and the rear three-dimensional represents the three-dimensional speed coordinate of the user; h and G are respectively a measurement vector and a measurement matrix of the related LoS path; e denotes an error vector caused by a measurement error;
n is the number of RRHs; r isn1Information sent for the user is routed through the LoSThe product of the measured time difference between the arrival of the nth RRH and the arrival of the 1 st RRH and the electromagnetic wave propagation velocity,
the product of the measured value of the frequency difference between the information sent for the user and the information arriving at the nth RRH and arriving at the 1 st RRH through the LoS path and the electromagnetic wave propagation speed, an＝[cosθncosφn,cosθnsinφn,sinθn]TThree-dimensional position coordinates b of nth RRHn＝[xb,n,yb,n,zb,n]T，cn＝[-sinφn,cosφn,0]T，dn＝[-sinθncosφn,-sinθnsinφn,cosθn]T，φnThe information sent for the user reaches the measured value of the azimuth angle of the nth RRH through the LoS path, thetanThe information sent for the user reaches the measurement value of the pitch angle of the nth RRH through the LoS path, and z is a full 0 vector of 1 multiplied by 3.
As a further technical solution of the present invention, in step 4, the environment mapping refers to estimating positions of all scatterers causing a single-hop NLoS path between the user and each RRH.
As a further technical scheme of the invention, the environment mapping model established in the step 4 is as follows:
wherein the content of the first and second substances,
is a three-dimensional column vector representing the three-dimensional position coordinates of a scatterer between the user and the nth RRH; h iss,nAnd Gs,nRespectively a measurement vector and a measurement matrix of a relevant single-hop NLoS path; e.g. of the types,nRepresenting an error vector caused by a measurement error;
n is the number of RRHs;
fn＝[cosθs,ncosφs,n,cosθs,nsinφs,n,sinθs,n]T，u°three-dimensional position coordinates b of the nth RRH as a three-dimensional column vector representing the user's positionn＝[xb,n,yb,n,zb,n]T，
The product of the measured value of the time difference between the information sent by the user and reaching the nth RRH through the single-hop NLoS path and reaching the 1 st RRH through the LoS path and the propagation speed of the electromagnetic wave, r1Is the distance between the user and the 1 st RRH, phis,nThe information sent for the user reaches the measured value of the azimuth angle of the nth RRH through a single-hop NLoS path, thetas,nAnd the information sent by the user reaches the pitch angle measured value of the nth RRH through a single-hop NLoS path.
As a further technical scheme of the invention, the joint position and velocity estimation model established in the step 2 and the environment mapping model established in the step 4 are solved based on an LS algorithm or a WLS algorithm based on a neural network in the steps 3 and 5.
Has the advantages that: the 3D positioning, speed measuring and environment mapping method based on the millimeter waves CRAN provided by the invention has the following advantages:
1. positioning algorithms in the existing millimeter wave communication system mostly depend on the result of beam training, for example, a feedback link is needed to provide arrival angle and departure angle information for a user, which cannot be realized in the initial access stage of a communication link. The positioning method provided by the scheme does not need extra overhead and can be fused into an initial access stage or an information transmission stage of a communication system;
2. the existing positioning algorithm does not realize joint position and speed estimation and environment mapping, the scheme adopts mixed measurement information (AoA, TDoA and FDoA) to establish a joint position and speed estimation and environment mapping model, and realizes high-precision positioning with lower model and algorithm complexity;
3. the existing multipoint positioning algorithm mainly adopts a radar system, the scheme combines the advantage that millimeter wave MIMO can obtain high-precision measurement information (AoA, TDoA and FDoA) with CRAN, and successfully implants the multipoint positioning technology into a 3D millimeter wave MIMO system.
Drawings
Fig. 1 is a flowchart of a method for 3D positioning, speed measurement and environment mapping based on millimeter waves CRAN according to an embodiment of the present invention.
Fig. 2 is a geometric schematic diagram of a position relationship of a 3D positioning, speed measurement and environment mapping method based on millimeter waves CRAN according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following detailed description is provided with reference to the accompanying drawings. The embodiment of the invention provides a millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method, as shown in FIG. 1, the method comprises the following steps:
step 1, each user sends an uplink orthogonal pilot signal to each radio frequency remote RRH, the RRH transmits the received signal to a central processing unit CU through a forward link, and the CU acquires the measurement information of each propagation path between each RRH and each user through the received signal.
Note that, as shown in fig. 2, the following description refers to
As the position coordinates of the kth user,
is the velocity coordinate of the kth user. Since the pilots transmitted by each user are orthogonal to each other, the embodiment of the present invention is described by taking only one user as an example. The three-dimensional position coordinate and the three-dimensional speed coordinate of the user to be estimated are respectively
And
the positions of N RRHs are known, and the three-dimensional position coordinate of the nth RRH is recorded as bn＝[xb,n,yb,n,zb,n]TWherein N is 1,2, …, N. For convenience of description, it is assumed that there is only one single-hop NLoS path between the user and each RRH, and the corresponding unknown scatterer position is recorded as
The aim of the embodiment of the invention is to estimate the position parameters according to the measurement information (TDoA, FDoA, AoA)
Truth values of measurement information (TDoA, FDoA, AoA) and truth values of position parameters
There is a correspondence relationship (if a represents a measurement value containing a measurement error, then a°Representing the true value for the measured value a):
(1) TDoA: for the LoS path, the product of the time of the information sent by the user reaching the nth RRH and the millimeter wave propagation speed is recorded as
For a single-hop NLoS path,
where ω represents the clock offset of the unknown user from all RRHs. The information sent by the user reaches the nth through LoS pathThe product of the real value of the difference between the RRH and the time when the RRH reaches the first RRH through the LoS path and the millimeter wave propagation speed is recorded as
The product of the real value of the time difference between the information sent by the user and arriving at the nth RRH through the single-hop NLoS path and arriving at the first RRH through the LoS path and the propagation speed of the millimeter wave is recorded as
By doing the difference, the unknown clock skew can be eliminated.
(2) FDoA: the FDoA related measurement information is obtained by derivation of TDoA related measurement information to time and is used for speed estimation of a user, so that only LoS path is needed and is recorded as
Wherein
(3) AoA: as shown in fig. 2, for the LoS path, the azimuth angle of the information sent by the user to the nth RRH is
A pitch angle of
For a single hop NLoS path, the azimuth angle is
A pitch angle of
And 2, screening LoS paths between the user and the RRHs by the CU by using the measurement information of each propagation path, and establishing a joint position and speed estimation model according to the measurement information of the relevant LoS paths.
It should be noted that the joint position and velocity estimation model is h ═ Gw + e, where h is Gw + e
Is an unknown user position and velocity vector;
wherein
And define an＝[cosθncosφn,cosθnsinφn,sinθn]T，cn＝[-sinφn,cosφn,0]T，
dn＝[-sinθncosφn,-sinθnsinφn,cosθn]T；
Wherein
And defines an all 0 vector with z of 1 x 3.
And 3, designing a joint estimation algorithm according to the joint position and speed estimation model established in the step 2, and acquiring the position and speed of the user.
It should be noted that, in the embodiment of the present invention, w is solved based on the WLS algorithm according to the joint position and velocity estimation model h ═ Gw + e, and the closed form solution of the w estimation value is w ═ G (G)TWG)-1GTWh, whereinW ═ to minimize variance of W estimate (E { ee)T})-1。
And 4, screening the single-hop NLoS paths between the user and all the RRHs by the CU by using the measurement information of each propagation path, and establishing an environment mapping model by combining the user position obtained in the step 3 and the measurement information of the relevant single-hop NLoS paths.
It should be noted that, for simplifying expression, in the embodiment of the present invention, one scatterer near the nth RRH is taken as an example for description, and the positioning of multiple scatterers can be obtained by simple extension, which is not described herein again. The environment mapping model is
Wherein
Is an unknown scatterer position vector;
wherein
fn＝[cosθs,ncosφs,n,cosθs,nsinφs,n,sinθs,n]T，
es,nError vectors caused by measurement errors.
And 5, designing an estimation algorithm according to the model to complete environment mapping.
It should be noted that the embodiment of the present invention maps according to the environment
Solving based on WLS algorithm
Closed form solution of the estimated value as sn＝(Gs,n TWs,nGs,n)-1Gs,n TWs,nhs,nIn which is caused to
W with minimum variance of estimated valuess,n＝(E{es,nes,n T})-1。
The above description is only for the specific embodiments of the present invention, but the scope of the present invention 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 invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (5)
1. A3D positioning, speed measuring and environment mapping method based on millimeter waves CRAN is characterized by comprising the following steps:
step 1, each user sends an uplink orthogonal pilot signal to each radio frequency remote RRH, the RRH transmits the received signal to a central processing unit CU through a forward link, and the CU acquires the measurement information of each propagation path between each RRH and each user through the received signal;
step 2, screening direct LoS paths between the user and a plurality of RRHs by the CU by using the measurement information of each propagation path, and establishing a joint position and speed estimation model according to the measurement information of the related LoS paths;
the established joint position and speed estimation model is as follows:
h＝Gw+e
wherein w isThe six-dimensional column vector represents the three-dimensional position coordinate of the user in the front three-dimensional mode and represents the three-dimensional speed coordinate of the user in the rear three-dimensional mode; h and G are respectively a measurement vector and a measurement matrix of the related LoS path; e denotes an error vector caused by a measurement error;
n is the number of RRHs; r isn1The product of the measured value of the time difference between the arrival of the information sent for the user at the nth RRH and the arrival at the 1 st RRH through the LoS path and the propagation speed of the electromagnetic wave,
the product of the measured value of the frequency difference between the information sent for the user and the information arriving at the nth RRH and arriving at the 1 st RRH through the LoS path and the electromagnetic wave propagation speed, an＝[cosθn cosφn,cosθn sinφn,sinθn]TThree-dimensional position coordinates b of nth RRHn＝[xb，n，yb,n,zb,n]T，cn＝[-sinφn，cosφn，0]T，dn＝[-sinθn cosφn，-sinθn sinφn，cosθn]T，φnThe information sent for the user reaches the measured value of the azimuth angle of the nth RRH through the LoS path, thetanThe information sent by the user reaches the pitch angle measurement value of the nth RRH through the LoS path, and z is a full 0 vector of 1 multiplied by 3;
step 3, solving the joint position and speed estimation model established in the step 2 to obtain the position and speed of the user;
step 4, screening out the single-hop non-direct NLoS paths between the user and all RRHs by the CU by using the measurement information of each propagation path, and establishing an environment mapping model by combining the user position obtained in the step 3 and the measurement information of the relevant single-hop NLoS paths;
the established environment mapping model is as follows:
wherein the content of the first and second substances,
is a three-dimensional column vector representing the three-dimensional position coordinates of a scatterer between the user and the nth RRH; h iss,nAnd Gs,nRespectively a measurement vector and a measurement matrix of a relevant single-hop NLoS path; e.g. of the types,nRepresenting an error vector caused by a measurement error;
n is the number of RRHs;
fn＝[cosθs,n cosφs,n,cosθs,n sinφs,n,sinθs,n]T，
three-dimensional position coordinates b of the nth RRH as a three-dimensional column vector representing the user's positionn＝[xb，n，yb，n，zb，n]T，
The product of the measured value of the time difference between the information sent by the user and reaching the nth RRH through the single-hop NLoS path and reaching the 1 st RRH through the LoS path and the propagation speed of the electromagnetic wave, r1Is the distance between the user and the 1 st RRH, phis,nSending for userThe information of (a) arrives at the measurement value of the azimuth angle of the nth RRH through the single-hop NLoS path, thetas,nThe information sent by the user reaches the measurement value of the pitch angle of the nth RRH through a single-hop NLoS path;
and 5, solving the environment mapping model established in the step 4 to complete environment mapping.
2. The millimeter wave CRAN-based 3D positioning, velocity measurement and environment mapping method according to claim 1, wherein in step 1, the measurement information of each propagation path between each RRH and each user obtained by the CU includes: the arrival angle AoA of the user uplink orthogonal pilot signal arriving at the RRH end, the time difference TDoA of the same user signal arriving at different RRHs and the frequency difference FDoA of the same user signal arriving at different RRHs.
3. The millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method according to claim 1, wherein in steps 2 and 4, there are two methods for the CU to screen LoS paths between the user and a plurality of RRHs and for the CU to screen single-hop NLoS paths between the user and all RRHs: (1) a CU sets a threshold value by utilizing the power estimation function of the RRH, the power exceeding the threshold value is judged as a LoS path, and the power lower than the threshold value is judged as a single-hop NLoS path; (2) and the CU classifies the LoS path and the single-hop NLoS path by utilizing the neural network through supervised learning, and trains the neural network by taking the measurement information as input.
4. The millimeter wave CRAN-based 3D positioning, velocity measurement and environment mapping method according to claim 1, wherein in step 4, the environment mapping refers to estimating the positions of all scatterers between the user and RRHs causing a single-hop NLoS path.
5. The millimeter wave CRAN-based 3D positioning, velocity measurement and environment mapping method according to claim 1, wherein in steps 3 and 5, the joint position and velocity estimation model established in step 2 and the environment mapping model established in step 4 are solved based on LS algorithm or WLS algorithm based on neural network.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910427793.8A CN110225449B (en) | 2019-05-22 | 2019-05-22 | Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910427793.8A CN110225449B (en) | 2019-05-22 | 2019-05-22 | Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110225449A CN110225449A (en) | 2019-09-10 |
| CN110225449B true CN110225449B (en) | 2021-01-12 |
Family
ID=67821695
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910427793.8A Expired - Fee Related CN110225449B (en) | 2019-05-22 | 2019-05-22 | Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110225449B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113709658B (en) * | 2020-05-22 | 2022-09-27 | 大唐移动通信设备有限公司 | Method, device and equipment for estimating moving speed of terminal |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6503452B2 (en) * | 2014-05-08 | 2019-04-17 | ノキア ソリューションズ アンド ネットワークス オサケユキチュア | Cloud based access network |
| US9973939B2 (en) * | 2015-09-25 | 2018-05-15 | Vivint, Inc. | UAV network design |
| US9609482B1 (en) * | 2015-12-07 | 2017-03-28 | Google Inc. | Cloud-coordinated location system using ultrasonic pulses and radio signals |
| CN105611629A (en) * | 2016-01-29 | 2016-05-25 | 中国海洋大学 | 60GHz millimeter wave non-line of sight identification and wireless fingerprint positioning method based on energy detection |
| CN105554882B (en) * | 2016-01-29 | 2019-01-18 | 中国海洋大学 | The identification of 60GHz non line of sight and wireless fingerprint positioning method based on energy measuring |
| CN105738866B (en) * | 2016-01-29 | 2018-03-13 | 中国海洋大学 | A kind of identification of 60GHz non line of sight and wireless fingerprint positioning method based on energy measuring |
| US10404369B2 (en) * | 2016-06-07 | 2019-09-03 | Siklu Communication ltd. | Systems and methods for using drones for determining line-of-sight conditions in wireless networks |
| US20170367097A1 (en) * | 2016-06-17 | 2017-12-21 | Electronics And Telecommunications Research Institute | Method and apparatus for handling radio link failure in mobile communication system |
| CN106850172A (en) * | 2017-01-18 | 2017-06-13 | 南京理工大学 | Millimeter wave mobile subscriber's localization method based on channel condition information |
| CN106714252B (en) * | 2017-02-28 | 2020-02-07 | 重庆邮电大学 | Cell switching method based on SDN (software defined network) controller under CRAN (building random Access network) architecture |
| CN208241704U (en) * | 2018-05-29 | 2018-12-14 | 广东奔潮科技发展有限公司 | A kind of real-time positioning night watching inspection system based on Bluetooth communication and cloud |
| CN109581345A (en) * | 2018-11-28 | 2019-04-05 | 深圳大学 | Object detecting and tracking method and system based on millimetre-wave radar |
-
2019
- 2019-05-22 CN CN201910427793.8A patent/CN110225449B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN110225449A (en) | 2019-09-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yuan et al. | Bayesian predictive beamforming for vehicular networks: A low-overhead joint radar-communication approach | |
| Chen et al. | A tutorial on terahertz-band localization for 6G communication systems | |
| CN113225275B (en) | Positioning information assistance-based channel estimation method and system | |
| CN110492911B (en) | Beam tracking method and system for unmanned aerial vehicle communication | |
| Du et al. | Integrated sensing and communications for V2I networks: Dynamic predictive beamforming for extended vehicle targets | |
| CN106357313B (en) | MIMO trunk channel outage probability calculation method towards UAV Communication | |
| Jiang et al. | Physics-based 3D end-to-end modeling for double-RIS assisted non-stationary UAV-to-ground communication channels | |
| Yu et al. | Efficient direct target localization for distributed MIMO radar with expectation propagation and belief propagation | |
| CN113115205B (en) | Distributed cooperative positioning method based on angle measurement | |
| CN110113088A (en) | A kind of divergence type numerical model analysis antenna system direction of arrival intelligence estimation method | |
| WO2024021440A1 (en) | Iterative focused millimeter-wave integrated communication and sensing method | |
| CN111628948A (en) | Radar communication integrated system, channel estimation method, device and storage medium | |
| Koivisto et al. | Channel parameter estimation and TX positioning with multi-beam fusion in 5G mmWave networks | |
| CN111181673B (en) | 3D wireless channel modeling method based on double-mobile scene | |
| CN110225449B (en) | Millimeter wave CRAN-based 3D positioning, speed measuring and environment mapping method | |
| Xu et al. | Data-driven beam management with angular domain information for mmWave UAV networks | |
| Lota et al. | MmWave V2V localization in MU-MIMO hybrid beamforming | |
| CN106792982B (en) | Multi-target direct positioning method based on self-adaptive clustering strategy | |
| CN115334524A (en) | Communication and radar target detection method based on omnidirectional intelligent super surface | |
| CN113162712B (en) | Multi-beam channel modeling method based on propagation diagram theory | |
| Mahyiddin et al. | Localization using joint AOD and RSS method in massive MIMO system | |
| CN115603789B (en) | Method for generating and tracking high-dynamic millimeter wave directional narrow beam | |
| CN115189989B (en) | Channel estimation method, electronic device and medium thereof | |
| CN115021864B (en) | Reconfigurable intelligent surface channel feedback system, electronic equipment and medium thereof | |
| Zhang et al. | A Novel Map Matching Based Localization Method for ISAC |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210112 |