CN114019450A - UWB-based indoor mobile robot positioning method - Google Patents

UWB-based indoor mobile robot positioning method Download PDF

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Publication number
CN114019450A
CN114019450A CN202111093246.4A CN202111093246A CN114019450A CN 114019450 A CN114019450 A CN 114019450A CN 202111093246 A CN202111093246 A CN 202111093246A CN 114019450 A CN114019450 A CN 114019450A
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base station
positioning
tag
uwb
ranging
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张继勇
舒洪睿
朱晨薇
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Hangzhou Fuyang Fuchuang Big Data Industry Innovation Research Institute Co ltd
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Hangzhou Fuyang Fuchuang Big Data Industry Innovation Research Institute Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • 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
    • 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
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • 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
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses an indoor mobile robot positioning method based on UWB, which comprises the following steps: s10, setting the position of the base station; s20, constructing a positioning system; s30, ranging: measuring the distance between each base station and the label; s40, constructing Kalman filtering and correcting the measurement data; s50, positioning and resolving to obtain a label coordinate; and S60, testing and comparing. The invention utilizes UWB technology and ADS-TWR ranging technology to ensure real-time performance and ranging precision of the positioning system, and ensures that the mobile robot can be accurately positioned indoors and autonomously navigated, and the positioning requirement precision is high.

Description

UWB-based indoor mobile robot positioning method
Technical Field
The invention belongs to the technical field of robots, and relates to an indoor mobile robot positioning method based on UWB.
Background
With the further development of social economy and the further improvement of the industrial automation level, the service robot has penetrated into all aspects of social life, wherein the indoor mobile robot occupies a large part, and different from a relatively structured industrial scene, a complex indoor environment puts higher requirements on the positioning of the mobile robot. How to flexibly and accurately position in an indoor scene is the most basic link in autonomous navigation of the mobile robot and is also the key problem for completing indoor tasks. The requirements for positioning are high positioning accuracy (sub-meter accuracy) and good real-time performance.
At present, the indoor positioning technology develops at home and shows the situations of multi-point blooming and hundred-bird singing: the positioning method comprises the following steps of a zigbee positioning technology, a WI-FI positioning technology, a bluetooth positioning technology, a radar positioning technology, an SLAM visual positioning technology, an Ultra-Wideband (UWB) technology and the like, wherein UWB signals have the advantages of ultrahigh resolution, multipath effect resistance, strong penetrating power and simple structure, and become the best indoor high-precision positioning technology at present. Compared with the characteristics of various indoor positioning technologies, the UWB system has the unique great advantages in the aspects of volume, power consumption, interference resistance, positioning accuracy and the like and the superstrong competitiveness of aoshiyangmongxiong.
The UWB positioning technology can reach centimeter-level or even higher positioning accuracy, and is completely attributed to the unique communication mechanism of the positioning technology. The traditional carrier signal modulation method is abandoned, and a nanosecond-level narrow pulse is adopted instead to directly transmit signals, so that the UWB system has the advantages of extremely wide spectrum range and low signal-to-noise ratio. The whole UWB system is a pure digital system, and the transmitter and the receiver do not contain traditional IF and RF circuits, so that the UWB system can be compressed to be small in practical situation. Therefore, the UWB system has great advantages of unique size, power consumption, interference resistance, positioning accuracy and the like and super-strong competitiveness of aod-looking and shouldering.
The UWB positioning tag is a movable positioned object, sends nanosecond pulse signals to the periphery, UWB base stations fixedly installed around receive and measure the pulse signals, and positioning measurement information such as the arrival time of the pulse signals is obtained through calculation of filtering, sliding correlation and the like.
Recently, in the field of domestic ultra-wideband positioning, a plurality of bright companies and teams emerge like spring bamboo shoots after rain. The Sichuan Chengdu Henggao company markets the UWB positioning system, UWB positioning software, SDK development platform, UWB positioning base station and label developed by the Sichuan Chengdu Henggao company, the product types are quite complete and rich, and the UWB positioning system can be highly integrated with video to realize real-time positioning. At the apple Inc. latest product release, the small peripheral AirTags are formally in the public place. The peripheral has a UWB wireless function, and can search for objects through mobile phone application; millet company also uses UWB technology in the public technology demonstration, and mainly aims at indoor high-precision positioning. Under the application scene of intelligent home, the UWB technology can use a mobile phone as a core to perform sensing ranging, and is a great innovation application.
The principles of UWB location technology are known first, and then do so. UWB positioning technology can adopt TOF (time of flight) ranging, TOF ranging method belongs to two-way ranging technology, and it mainly uses time of flight of signal between two transceivers to measure distance between nodes. The module generates a separate timestamp from the start. The transmitter of module a transmits a1 on its time stamp a pulse signal of the nature of the request, and module B transmits a signal of the nature of the response at time B2, received by module a at its time stamp a 2. The flight time of the pulse signal between the two modules can be calculated through a formula, and therefore the flight distance can be determined. The indoor positioning principle of UWB is similar to satellite principle, that is, several positioning base stations with known coordinates are arranged indoors, the person to be positioned carries a positioning tag, the tag emits pulses according to a certain frequency, the distance measurement is continuously carried out with several base stations, and the position of the tag is determined through a certain positioning calculation algorithm. However, the indoor environment is complicated, many obstacles are present, and a non line of sight (NLOS) situation in which a signal of a certain base station is completely blocked is likely to occur. The positioning calculation algorithms widely used in the UWB positioning system at present generally include the following algorithms: least Square Estimation (LSE), Fang algorithm, Chan algorithm and Taylor algorithm, wherein the LSE can search the optimal function matching of data by minimizing the sum of squares of errors, and can further reduce errors caused by NLOS.
In the prior art, due to the characteristics of more obstacles, pedestrian traffic and the like in an indoor environment, a general wireless positioning technology is difficult to achieve a higher positioning technology, and an Ultra Wide Band (UWB) technology has the characteristics of short pulse, high multipath resolution and high positioning precision and is suitable for being applied to indoor positioning. However, UWB is still not perfect, and UWB positioning requires more than 3 fixed base stations, so that under the condition of non line of sight (NLOS) where signals of a certain base station are completely blocked, the situation that positioning cannot be completed or positioning accuracy is poor occurs when the number of visible base stations is reduced. The UWB technology is now urgently needed to reduce non-line-of-sight errors as much as possible and improve system positioning accuracy.
Disclosure of Invention
In order to solve the problems, the technical scheme provided by the invention is to design a high-precision indoor positioning system of the mobile robot by using a UWB technology. On one hand, the real-time performance and the ranging precision of the positioning system are ensured by adopting the ADS-TWR ranging technology; the ADS-TWR method ranging process comprises the following steps: firstly, a tag requests a frame to a sending base station; the base station starts timing after receiving the request frame, and sends a response frame to the tag after delaying; the tag starts timing after receiving the response frame, writes time points of the sending and receiving signals into an end frame, and sends the end frame to the base station after delaying; and the base station receives the termination frame and then indicates that the ranging is finished.
In order to achieve the aim, the technical scheme of the invention is an indoor mobile robot positioning method based on UWB, which comprises the following steps:
s10, setting the position of the base station;
s20, constructing a positioning system;
s30, ranging: measuring the distance between each base station and the label;
s40, constructing Kalman filtering and correcting the measurement data;
s50, positioning and resolving to obtain a label coordinate;
and S60, testing and comparing.
Preferably, the S10 sets the base station position, including determining that the indoor site size is a × b, and sets four UWB positioning base stations thereon, respectively placed at four positions of (a1, b1), (a2, b2), (a3, b3), (a4, b4), and setting the height of the UWB positioning base station as h, wherein the base stations are divided into normal base stations and communication base stations, and the normal base stations include: the mobile robot comprises a second base station (a2, b2, h), a third base station (a3, b3, h) and a fourth base station (a4, b4, h), wherein the communication base station comprises a first base station (a1, b1, h), a label is installed at the top end of the mobile robot, and the communication base station is connected with an upper computer through a serial port.
Preferably, the S20 positioning system comprises a tag and a base station, wherein the tag and the base station comprise a single chip microcomputer and a DWM1000 communication module, and the tag or the base station is configured; the base station is set as an active end, the label is set as a passive end, the first base station serves as a core, and all behavior modes are concentrated on the first base station.
Preferably, the S30 ranging includes recording a time stamp of transmission and reception information for each message, and marking different delays and round trip times, thereby calculating a time of flight of information between each base station and the tag, and thus calculating a distance.
Preferably, the S30 ranging includes the following steps:
s31, initializing mobile tag: sending a POLL request frame to all base stations through the mobile tag, starting timing after the first base station receives the request frame, and delaying for treplyB1Sending a REPLY response frame to the label; the tag starts timing after receiving the response frame, writes the time points of the sending and receiving signals into a FINAL termination frame, and delays treplyA1Then sending to each base station; after receiving the termination frame, the first base station indicates that the ranging between the first base station and the tag is finished;
s32, according to different set response time, the first base station orders the second base station, the third base station and the fourth base station to send response frames to the label in sequence, the subsequent steps are the same as the first base station, and the last ranging information is transmitted to the communication base station, namely the first base station, through UWB;
and S33, the first base station transmits the information to the upper computer through a serial port.
Preferably, the S40 constructing kalman filtering to correct the measurement data includes the following steps:
s41, constructing a Kalman filter based on MATLAB, initializing various parameters, setting tracking points, system state initial values, state transition matrix initial values, sampling frequency and iteration times of the Kalman filter, and inputting the distance di (t) between each base station and a label, (i is 1, 2, 3 and 4);
s42, performing Kalman filtering on the distance signal by using a state vector equation, and estimating an NLOS error value Ni (t);
s43, then remove the non-line-of-sight error from the initial distance measurement value di (t) to obtain the accurate distance value di (t).
Preferably, the S50 positioning solution is used to find the tag coordinates, which includes using the kalman filtered data di (t) as the input of the least square method, and searching for the optimal function matching of the data by minimizing the sum of squares of the errors, so as to finally find the tag coordinates (xi, yi, zi).
Preferably, the S60 test comparison includes comparing the moving route of the mobile robot with the calculated real-time coordinate route, determining whether the error exceeds a preset maximum value, if so, modifying the response time of the ADS-TWR, reducing the time for tag ranging, and continuing to implement S30-S60 until the error is within a preset range.
The invention has at least the following specific beneficial effects:
1. sources of UWB positioning system ranging errors include errors caused by clock drift of the crystal oscillator. The crystal oscillator clock drift can affect the measurement of the signal sending and receiving time points, and then affect the accuracy of distance measurement. Although the distance measurement mode of the two-way distance measurement of the UWB positioning system can eliminate the influence of incomplete synchronization between nodes, the influence of crystal oscillator clock drift cannot be eliminated. The invention uses asymmetric bilateral two-way ranging (ADS-TWR) without clock synchronization between the base station and the label and between the base station and the base station, has more flexibility for time control in the ranging process, and ensures the real-time performance of the positioning system by optimizing the response time of each base station for the positioning system with four base stations.
2. Because the indoor environment is complicated, signal transmission is easily blocked by walls and indoor personnel, and the phenomenon of non line of sight (NLOS) transmission is generated, thereby causing great interference to system positioning. At present, the development optimization direction of the UWB positioning system algorithm is to reduce the influence of NLOS as much as possible. The invention provides a Least Square Estimation (LSE) mode of combined Kalman filtering on the basis of a pre-research algorithm.
Drawings
FIG. 1 is a flowchart illustrating the steps of a UWB based indoor mobile robot positioning method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the S30 distance measurement of the UWB-based indoor mobile robot positioning method according to the embodiment of the invention;
FIG. 3 is a schematic diagram of a multi-base-station ranging timing sequence of an indoor mobile robot positioning method based on UWB according to an embodiment of the present invention;
fig. 4 is a flowchart of S40 of a UWB-based indoor mobile robot positioning method according to an embodiment of the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
On the contrary, the invention is intended to cover alternatives, modifications, equivalents and alternatives which may be included within the spirit and scope of the invention as defined by the appended claims. Furthermore, in the following detailed description of the present invention, certain specific details are set forth in order to provide a better understanding of the present invention. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details.
The invention is first defined and explained below:
OLL package: requesting information;
RESP package: response information;
FINAL packet: a termination message;
positioning a label: the UWB positioning tag is carried in target personnel and materials and periodically sends an uplink UWB positioning pulse signal.
Positioning a base station: the UWB positioning base station is fixedly arranged around the environment and used for receiving pulse signals of the UWB positioning tags to obtain high-precision positioning data.
Referring to fig. 1, a technical solution of the present invention, which is an embodiment of the present invention, is a flowchart of steps of a UWB-based indoor mobile robot positioning method, including the following steps:
s10, setting the position of the base station;
s20, constructing a positioning system;
s30, ranging: measuring the distance between each base station and the tag 10;
s40, constructing Kalman filtering and correcting the measurement data;
s50, positioning and resolving to obtain the coordinates of the tag 10;
and S60, testing and comparing.
S10 sets the base station position, including determining the indoor site size as a × b, and setting four UWB positioning base stations thereon, respectively placed at four positions of (a1, b1), (a2, b2), (a3, b3), (a4, b4), and setting the height of the UWB positioning base station as h, wherein the base stations are divided into normal base stations and communication base stations, and the normal base stations include: the mobile robot comprises a second base station 22(a2, b2, h), a third base station 23(a3, b3, h) and a fourth base station 24(a4, b4, h), wherein the communication base stations comprise the first base station 21(a1, b1, h), a tag 10 is installed at the top end of the mobile robot, and the communication base stations are connected with an upper computer through serial ports.
The S20 positioning system comprises a tag 10 and a base station, wherein the tag 10 and the base station comprise a single chip microcomputer and a DWM1000 communication module and are configured to be the tag 10 or the base station; the base station is set as the active end, the tag 10 is set as the passive end, the first base station 21 serves as the core, and all behavior patterns are concentrated on the first base station 21.
S30 ranging, which includes recording time stamps of transmission and reception information for each message, and marking different delays and round trip times, thereby calculating the time of flight of information between each base station and the tag 10, and thus calculating the distance.
In conjunction with the timing diagrams of fig. 2 and 3, the S30 ranging method includes the following steps:
s31, initializing mobile tag 10: sending a POLL request frame to all base stations through the mobile tag 10, starting timing after the first base station 21 receives the POLL request frame, and delaying for treplyB1A REPLY response frame is sent to the tag 10; the tag 10 starts timing after receiving the response frame, writes the time points of the sending and receiving signals into a FINAL frame, and delays treplyA1Then sending to each base station; after the first base station 21 receives the termination frame, it indicates that the ranging between the first base station 21 and the tag 10 is finished;
s32, according to the different set response time, the first base station 21 orders the second base station 22, the third base station 23 and the fourth base station 24 to sequentially send response frames to the tag 10, the subsequent steps are the same as the first base station 21, and the last ranging information is transmitted to the communication base station, i.e. the first base station 21, through UWB;
and S33, the first base station 21 transmits the information to the upper computer through a serial port.
S40, constructing Kalman filtering and correcting measurement data, and the method comprises the following steps:
s41, constructing a kalman filter based on MATLAB, initializing various parameters, setting tracking points, system state initial values, state transition matrix initial values, sampling frequencies, and iteration times of the kalman filter, and inputting the distance di (t) (i ═ 1, 2, 3, 4) between each base station and the tag 10;
s42, performing Kalman filtering on the distance signal by using a state vector equation, and estimating an NLOS error value Ni (t);
s43, then remove the non-line-of-sight error from the initial distance measurement value di (t) to obtain the accurate distance value di (t).
Referring to fig. 4, a flow diagram of the S40 Kalman filter is shown.
S50 positioning and resolving are carried out to obtain the coordinates of the tag 10, the Kalman filtered data Di (t) is used as the input of a least square method, the optimal function matching of the data is searched through minimizing the sum of squares of errors, and finally the coordinates (xi, yi, zi) of the tag 10 are obtained.
And S60, comparing the moving line of the mobile robot with the calculated real-time coordinate route, judging whether the error exceeds a preset maximum value, if so, modifying and optimizing the response time of ADS-TWR, reducing the distance measurement time of the tag 10, and continuing to implement S30-S60 until the error is within a preset range.
Referring to fig. 1, fig. 2 and table 1, the ranging process of the present invention is intuitively explained. The sequence numbers of the actions in Table 1 correspond to the numbers in FIG. 2, which is also the flow sequence.
TABLE 1
Figure BDA0003268345880000081
Figure BDA0003268345880000091
Aiming at the problems of poor flexibility and low precision of the indoor positioning mode of the current mobile robot, the invention designs a high-precision indoor positioning method of the mobile robot by utilizing the UWB technology, and on one hand, the real-time performance and the ranging precision of a positioning system are ensured by adopting the ADS-TWR ranging technology; the ADS-TWR method ranging process comprises the following steps: firstly, a tag 10 requests a frame to a transmitting base station; the base station starts timing after receiving the request frame, and the time delay t is passedreplyB1Sending a response frame to the tag 10; the tag 10 starts timing after receiving the response frame, writes the time points of the transmission and reception signals into the termination frame, and delays treplyA1Then sending the data to a base station; and the base station receives the termination frame and then indicates that the ranging is finished.
A communication base station: after positioning starts, the tag 10 sends a POLL packet to each base station, the main base station (the first base station 21) performs ADS-TWR ranging on the currently positioned tag 10, sends a RESP packet to the tag 10, and then receives a FINAL packet returned by the tag 10. And after receiving, informing each secondary base station to carry out ranging, obtaining the ranging value di (t) of each secondary base station, and transmitting the information to the upper computer through a serial port.
A common base station: the secondary base station is always in a monitoring state, and after receiving a ranging starting instruction of the main base station, the secondary base station sends an RESP (resource response protocol) packet to the tag 10 for ranging; and finally, receiving a FINAL packet returned by the tag 10 to perform ranging calculation, and returning a ranging value to the base station.
The label 10: the tag 10 is in a state of being monitored all the time, and after receiving the ranging POLL packet of the base station, the tag sends an RESP packet, and then after receiving the FINAL packet of the base station, the tag sends an ACK packet.
And on the other hand, a Kalman filtering (Kalman) method is adopted for positioning, non-line-of-sight errors are filtered out, the positioning precision of the system is ensured, and then a least square method (LES) is used for positioning and analyzing to obtain coordinates. Kalman filtering is an algorithm that uses the system state equation to make an optimal estimate of the system state from the input data and the observed data of the system. The method aims to reduce the influence of measurement noise as much as possible by using the current measurement value and the last estimation value, so that the measurement data is corrected infinitely approaching to a real value, and the effect of reducing NLOS can be achieved.

Claims (8)

1. An indoor mobile robot positioning method based on UWB is characterized by comprising the following steps:
s10, setting the position of the base station;
s20, constructing a positioning system;
s30, ranging: measuring the distance between each base station and the label;
s40, constructing Kalman filtering and correcting the measurement data;
s50, positioning and resolving to obtain a label coordinate;
and S60, testing and comparing.
2. The method as claimed in claim 1, wherein the S10 sets the base station location, including determining that the indoor site size is a x b, and sets four UWB positioning base stations thereon, respectively placed at four locations of (a1, b1), (a2, b2), (a3, b3), (a4, b4), and sets the UWB positioning base station height h, wherein the base stations are divided into a normal base station and a communication base station, the normal base station including: the mobile robot comprises a second base station (a2, b2, h), a third base station (a3, b3, h) and a fourth base station (a4, b4, h), wherein the communication base station comprises a first base station (a1, b1, h), a label is installed at the top end of the mobile robot, and the communication base station is connected with an upper computer through a serial port.
3. The method of claim 2, wherein the S20 positioning system comprises a tag and a base station, each of which comprises a single chip microcomputer and a DWM1000 communication module configured as a tag or a base station; the base station is set as an active end, the label is set as a passive end, the first base station serves as a core, and all behavior modes are concentrated on the first base station.
4. The method of claim 3, wherein the S30 ranging comprises recording the time stamp of the sending and receiving information of each message, marking different time delay and round trip time, thereby calculating the flight time of information between each base station and the tag, and further calculating the distance.
5. The method of claim 3, wherein the S30 ranging comprises the following steps:
s31, initializing mobile tag: sending a POLL request frame to all base stations through the mobile tag, starting timing after the first base station receives the request frame, and delaying for treplyB1Sending a REPLY response frame to the label; the tag starts timing after receiving the response frame, writes the time points of the sending and receiving signals into a FINAL termination frame, and delays treplyA1Then sending to each base station; after receiving the termination frame, the first base station indicates that the ranging between the first base station and the tag is finished;
s32, according to different set response time, the first base station orders the second base station, the third base station and the fourth base station to send response frames to the label in sequence, the subsequent steps are the same as the first base station, and the last ranging information is transmitted to the communication base station, namely the first base station, through UWB;
and S33, the first base station transmits the information to the upper computer through a serial port.
6. The method of claim 5, wherein said S40 constructs Kalman filtering, amending the measurement data, comprises the steps of:
s41, constructing a Kalman filter based on MATLAB, initializing various parameters, setting tracking points, system state initial values, state transition matrix initial values, sampling frequency and iteration times of the Kalman filter, and inputting the distance di (t) between each base station and a label, (i is 1, 2, 3 and 4);
s42, performing Kalman filtering on the distance signal by using a state vector equation, and estimating an NLOS error value Ni (t);
s43, then remove the non-line-of-sight error from the initial distance measurement value di (t) to obtain the accurate distance value di (t).
7. The method of claim 6, wherein the S50 positioning solution for finding the tag coordinates includes using kalman filtered data di (t) as an input of a least square method, and searching for an optimal function match of the data by minimizing a sum of squares of errors, and finally finding the tag coordinates (xi, yi, zi).
8. The method of claim 7, wherein the S60 test comparison includes comparing the moving route of the mobile robot with the calculated real-time coordinate route, determining whether the error exceeds a preset maximum value, if so, modifying the response time of the ADS-TWR, reducing the time for tag ranging, and continuing to implement S30-S60 until the error is within a preset range.
CN202111093246.4A 2021-09-17 2021-09-17 UWB-based indoor mobile robot positioning method Withdrawn CN114019450A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115002663A (en) * 2022-06-09 2022-09-02 长春理工大学 UWB-based method for determining static pointing direction of head of intelligent vehicle
CN116437288A (en) * 2023-05-04 2023-07-14 青岛柯锐思德电子科技有限公司 Method for selecting LOS base station algorithm design based on signal strength
CN117194854A (en) * 2023-11-01 2023-12-08 辽宁天衡智通防务科技有限公司 Three-dimensional positioning method and device based on improved Chan algorithm

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115002663A (en) * 2022-06-09 2022-09-02 长春理工大学 UWB-based method for determining static pointing direction of head of intelligent vehicle
CN116437288A (en) * 2023-05-04 2023-07-14 青岛柯锐思德电子科技有限公司 Method for selecting LOS base station algorithm design based on signal strength
CN116437288B (en) * 2023-05-04 2024-02-09 青岛柯锐思德电子科技有限公司 Method for selecting LOS base station algorithm design based on signal strength
CN117194854A (en) * 2023-11-01 2023-12-08 辽宁天衡智通防务科技有限公司 Three-dimensional positioning method and device based on improved Chan algorithm
CN117194854B (en) * 2023-11-01 2024-02-27 辽宁天衡智通防务科技有限公司 Three-dimensional positioning method and device based on improved Chan algorithm

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