CN112566028A - Indoor robot positioning method based on UWB - Google Patents

Indoor robot positioning method based on UWB Download PDF

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CN112566028A
CN112566028A CN202011412172.1A CN202011412172A CN112566028A CN 112566028 A CN112566028 A CN 112566028A CN 202011412172 A CN202011412172 A CN 202011412172A CN 112566028 A CN112566028 A CN 112566028A
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positioning
time
clock
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CN112566028B (en
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马国军
冷加俊
顾琪伟
朱琎
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Jiangsu University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—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
    • H04W4/30—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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H04W56/001—Synchronization between nodes
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses an indoor robot positioning method based on UWB, which comprises the steps of setting a clock reference base station, calculating clock offset of other base stations according to the clock reference base station when time of the base station is taken as standard in each time synchronization, calculating time offset when positioning between a robot and the base station on the basis of the clock offset of the base station, and correcting the robot in time according to the acquired time offset in the subsequent positioning process between the robot and the base station. The invention establishes a clock model for each base station to realize the correction of the local arrival time of the positioning signal, provides a method for decentralized calculation and improves the real-time performance of positioning; the method also avoids the defect of channel occupation time length in the local arrival time correction of the TWR method in the prior art, saves energy consumption and lays a cushion for the later expansion performance.

Description

Indoor robot positioning method based on UWB
Technical Field
The invention relates to the field of indoor wireless communication and robot positioning systems, in particular to an indoor robot positioning method based on UWB (ultra Wide band).
Background
The intelligent robot becomes the wind gap wave tip of the industry, and from the cleaning robot, a family accompanying robot, a meal delivery robot and the like continuously enter the public sight. In discussing whether these robots can solve practical problems, autonomous positioning navigation technology is continuously attracting attention in the industry as the first step of robot intelligence.
Wireless location systems are attracting attention as one of the most attractive location technologies. UWB has recently been "reused" as an accurate, secure, real-time location technology, which is not comparable to other wireless technologies (e.g., Wi-Fi, bluetooth, and GPS).
UWB technology can achieve centimeter-level positioning accuracy, and UWB has been increasingly applied to the field Of high-precision indoor positioning due to its high time resolution, and common positioning methods include toa (time Of arrival), rssi (received Signal Strength indication), aoa (time Difference Of arrival), and tdoa (angle Of arrival).
In view of the high time resolution of UWB, two approaches, TOA and TDOA, are mainly explored. The TOA method requires clock synchronization of all devices, as compared to TDOA which requires only base station clock synchronization. For clock synchronization, both wired and wireless clock synchronization may be used. When the indoor space is too large, a large number of cables and clock synchronizers need to be laid for wired clock synchronization, the layout is complicated, and the cost is too high; the wireless clock synchronization optimizes the layout method, but at present, a lot of wireless clock synchronization based on UWB mainly adopts a TWR (Two-Way Ranging) method, and Two parties need to exchange a lot of information, so that the channel occupation is long, and along with the increase of base stations, the channel occupation is multiplied, so that the expansion and positioning real-time capability is reduced.
TDOA is used as a common method of a positioning system, except the problems, namely system NLOS and equation nonlinearity, the system equation or the observation equation needs to be subjected to Taylor expansion by adopting the traditional EKF, first-order approximation is reserved, linearization errors are introduced, and the calculation amount is large and is not beneficial to practical application.
Disclosure of Invention
The invention aims to provide an indoor robot positioning method based on UWB (ultra wide band), which solves the technical problems of channel occupation, low tag expansibility, complex environment layout and large calculation amount in the existing indoor robot positioning technology.
In order to solve the technical problems, the invention adopts the following technical scheme:
an indoor robot positioning method based on UWB includes:
step 1: constructing an indoor positioning system, arranging at least four base stations and a mobile tag attached to a robot, wherein the robot takes the mobile tag as a coordinate point of the robot;
step 2: taking any one of all base stations as a clock reference base station, when the base station acquires a first positioning signal sent by a robot, accumulating and timing all the base stations from zero, recording the accumulated timing as the working time of the base station, and when the base station receives the signal, taking the working time of the current base station as the local arrival time of the signal;
and step 3: the clock reference base station transmits synchronous signals to other base stations, and the other base stations establish a clock model by utilizing an interpolation synchronization algorithm based on the local time and the synchronous times of the synchronous signals;
the robot transmits positioning signals to all base stations, and the base stations except the clock reference base station extrapolate the clock offset of the positioning signals based on the local arrival time of the positioning signals, the positioning times and the clock model;
the base stations except the clock reference base station carry out clock offset correction on the local arrival time of the positioning signal by subtracting the clock offset of the positioning signal from the local arrival time of the positioning signal;
and 4, step 4: the base station sends the local arrival time of the positioning signal corrected in the step 3 to the robot, and the robot subtracts the local arrival time of the positioning signal sent by the time reference base station from the local arrival time of the corrected positioning signal sent by the base stations except the time reference base station one by one to obtain a plurality of TDOA values;
and 5: establishing a motion model of the robot, and acquiring mobile tag coordinates by using a UKF (unscented Kalman Filter) algorithm based on a plurality of TDOA (time difference of arrival) values;
step 6: and (5) accumulating the synchronization times and the positioning times, repeatedly executing the steps 3 to 5 by the clock reference base station by taking the interval period of the synchronization signal as an interval and the positioning signal interval period of the robot by taking the interval period of the positioning signal as an interval, and acquiring the coordinates of the mobile tag in real time until the positioning is stopped.
Further, the step 3 of establishing a clock model by the other base stations by using an interpolation synchronization algorithm based on the local arrival time of the synchronization signal is specifically as follows:
Figure BDA0002818464100000031
wherein n is a base station serial number; k is the number of synchronization times; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tsn,kThe local arrival time of a synchronizing signal is the nth base station when the kth synchronization is carried out; epsilonn,kFor a total period of k times the synchronization signal is transmitted,
Figure BDA0002818464100000032
τncommunication propagation delay for base station n; rhosn,kThe nth base station is the nth base station, and the clock drift rate is obtained during the k-th synchronization; f. ofsSpacing frequencies for synchronization signals; Δ tn,k-1The total clock offset of the local arrival time of the synchronous signal at the k-1 synchronization time of the nth base station in the previous time.
Further, in step 3, the specific formula of the clock offset of the base station based on the positioning signal and the clock model extrapolated positioning signal is as follows:
ρn,i＝Δtn,k+ρsn,k(tn,i-tsn,k)
wherein n is a base station serial number; k is the number of synchronization times; i is the positioning times; rhon,iClock skew of extrapolated positioning signal of local arrival time of positioning signal at ith positioning for base station n; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tn,iThe total clock offset of the local arrival time of the positioning signal at the ith positioning time is the nth base station; t is tsn,kFor the nth base station, the local arrival time of the synchronization signal is synchronized at the kth time.
Further, in step 5, in the process of obtaining the mobile tag coordinates by using the UKF filtering algorithm based on the plurality of TDOA values, the distance difference formula for obtaining the coordinate solution is as follows:
Figure BDA0002818464100000041
wherein n is a base station serial number; i is the positioning times; Δ dn1,iThe difference value between the measured distance of the base station and the measured distance of the clock reference base station is obtained when the nth base station and the clock reference base station are positioned for the ith time; c is the UWB signal transmission speed; Δ tiTDOA value for the ith location;
Figure BDA0002818464100000042
the local arrival time of the positioning signal corrected by the nth base station is obtained; t is t1,iThe local arrival time of the positioning signal of the base station is referenced to the clock.
Compared with the prior art, the invention has the following advantages:
1) the invention realizes the interpolation clock synchronization algorithm by using the time reference base station, realizes the wireless clock synchronization of the base station, has simple scene arrangement and reduces the cost;
2) the clock model is established for each base station, so that the local arrival time of the positioning signal is corrected, a scattered calculation method is provided, and the positioning instantaneity is improved; the defect of channel occupation time length in the local arrival time correction of the TWR method in the prior art is also avoided, energy consumption is saved, and meanwhile, the method lays a cushion for later expansion performance;
3) the invention utilizes TDOA combined with UKF algorithm to realize accurate indoor positioning of the robot, improve the adaptive capacity of the system and reduce the complexity of robot positioning calculation.
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The features and advantages of the present invention will be more clearly understood by reference to the accompanying drawings, which are illustrative and not to be construed as limiting the invention in any way, and in which:
FIG. 1 is a block diagram of a hardware system carrying the method of the present invention;
FIG. 2 is a flow chart of the method of the present invention for performing clock modeling based on synchronization signals and local arrival time correction based on positioning signals;
FIG. 3 is a UKF indoor positioning process based on TDOA in the method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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 invention.
The embodiment of the invention provides an indoor robot positioning method based on UWB, which can avoid signal collision and realize robot positioning in real time through distributed clock calculation. Fig. 1 is a hardware system block diagram of an UWB-based indoor robot positioning system carrying the method of the present invention, comprising a base station and a robot, wherein the base station and the robot perform wireless communication through clock synchronization between the base stations, thereby implementing a final positioning process inside the robot. The base station and the robot select a transceiver module designed based on a Decawave DW1000 chip, and the transceiver module integrates an antenna, an RF circuit, a power supply management circuit and a clock circuit. The robot carries a robot core control MCU, and the robot is controlled to move, and measurement data are collected by wireless communication and are resolved, so that the real-time positioning of the robot is realized. The location method of the present invention is not limited to operation in the hardware system block diagram shown in fig. 1.
The specific implementation method provided by the invention comprises the following steps:
step S1: four base stations are arranged in an indoor environment according to requirements: base station 1, base station 2, base station 3, and base station 4;
in order to optimize the positioning effect, a proper coordinate origin is selected through multi-direction measurement indoors, the coordinate origin is expanded into a three-dimensional space coordinate system, 4 fixed coordinate positions which are not all on one plane are determined in the space coordinate system, 4 base stations are fixed at the coordinate positions, and then the initial position of the robot is recorded.
The robot and the base station are configured by Unique identifiers (EUI) of single MCUs used by the nodes, the base station 1 is set as a clock reference base station through the EUI of each base station and the robot, the UWB node of the robot is set as a positioning node, and the base stations 2, 3 and 4 are receiving nodes.
Step S2: the robot issues a first positioning signal to all base stations, the positioning signal is used as an awakening signal to awaken all base stations, all base stations start to accumulate and time from zero, the accumulated time is recorded as the working time of the base stations, and when the base stations receive the signal, the working time of the current base station is used as the local arrival time of the signal, for example: when the base station receives the synchronous signal, the working time of the current base station is the local arrival time of the synchronous signal of the current synchronous signal; when the base station receives the positioning signal, the working time of the current base station is the local arrival time of the positioning signal of the current positioning signal.
The base station 1 is defined as a clock reference base station, the time of the base station is used as a global clock, the base station 1 starts to periodically transmit a synchronous signal, the base stations 2, 3 and 4 receive data, and due to the limitation of transmission serial numbers, a transmitter EUI, a received serial number and a synchronous receiving clock are used for linearization processing, and interpolation clock modeling is started.
FIG. 2 shows the flow of step S3, step S3: the robot continuously transmits a positioning signal, and all base stations continuously update or position the model by judging whether the received signal is a synchronous signal or the positioning signal.
Achieving ideal clock synchronization for all base stations is difficult to achieve because every UWB device contains a crystal oscillator that generates clocks at different frequencies and is difficult to achieve uniformity. In order to enable the clocks of the base stations to achieve the consistent effect simply and quickly, the invention adopts a reference clock as a global clock to carry out interpolation operation to establish a clock model for each base station.
The total period of the kth time clock synchronization of base station 1 and base stations 2, 3 and 4 is epsilon2,k、ε3,k、ε4,kThe local arrival time of the base station synchronization signal is ts2,k、ts3,k、ts4,kThe transmission frequency of the synchronization signal of the base station 1 is set to fsThe total clock offset Δ t of the nth base station can be calculated by the formula (1)n,kAnd clock drift ρn,k：
Figure BDA0002818464100000061
Wherein n is a base station serial number; k is the number of synchronization times; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tsn,kThe local arrival time of a synchronizing signal is the nth base station when the kth synchronization is carried out; epsilonn,kFor a total period of k transmissions of the synchronization signal, τnCommunication propagation delay for base station n; rhosn,kFor base station n, clock drift rate at kth synchronization, fsSpacing frequencies for synchronization signals; Δ tn,k-1The total clock offset of the local arrival time of the synchronous signal at the k-1 synchronization time of the nth base station in the previous time.
Figure BDA0002818464100000071
The above process is an interpolation modeling method, according to the above model, the local arrival time of the positioning signal and the synchronization update model will be measured subsequently, when the base station receives the signal, the EUI is used to judge whether the signal is a synchronization signal or a positioning signal:
when the received synchronous signal is the synchronous signal, updating a clock model by adopting the clock modeling method;
when a positioning signal is received, the base station extrapolates the clock offset of the positioning signal by equation (3) based on the local arrival time of the positioning signal, and the clock model:
ρn,i＝Δtn,k+ρsn,k(tn,i-tsn,k) (3)
wherein n is a base station serial number; k is the number of synchronization times; i is the positioning times; rhon,iClock skew of extrapolated positioning signal of local arrival time of positioning signal at ith positioning for base station n; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tn,iThe total clock offset of the local arrival time of the positioning signal at the ith positioning time is the nth base station; t is tsn,kFor the nth base station, the local arrival time of the synchronization signal is synchronized at the kth time.
And finally, the base stations except the clock reference base station carry out clock offset correction on the local arrival time of the positioning signal by subtracting the clock offset of the positioning signal from the local arrival time of the positioning signal, and the base station sends the corrected local arrival time of the positioning signal to the robot.
At this time, the robot acquires a local arrival time value of a positioning signal between the base station and the robot, and positioning by adopting the TOA method requires clock synchronization of the base station and the robot, so that indoor positioning is performed by adopting the TDOA method in order to avoid complex calculation.
Step S4: and (3) executing positioning, filtering the data packets transmitted by the four base stations by a preset threshold value through the robot, and subtracting the corrected positioning signal local arrival time values sent from the base stations 2, 3 and 4 from the positioning signal local arrival time value of the base station 1 respectively to obtain 3 TDOA values when 4 corrected positioning signal local arrival time values under the same sequence number are collected.
FIG. 3 shows the flow of step S5, step S5: the method comprises the steps of utilizing the TDOA value to achieve UKF (unscented Kalman Filter) filtering and configure the motion state of the robot, setting the robot to move at a constant speed in the implementation mode, introducing an acceleration sensor to judge the motion state of the robot, introducing an UKF algorithm to position after the robot starts to execute a motion command, and utilizing the optimal constant speed state as an initial state to initialize the UKF of the robot by utilizing a motion model configured by the robot.
Setting a three-dimensional state vector s based on the motion modeliAs shown in formula (4).
Figure BDA0002818464100000081
In the formula (4), i is a positioning frequency index, x, y and z represent the space three-dimensional coordinates of the robot,
Figure BDA0002818464100000082
Figure BDA0002818464100000083
representing the moving speed of the robot in three directions in the three-dimensional space, and the calculation dimension n is 6 at this moment.
Since the coordinate solution is calculated based on the distance formula, the distance difference formula can be obtained by multiplying the collected TDOA value by the UWB signal transmission speed c, as shown in formula (5):
Figure BDA0002818464100000084
wherein n is a base station serial number; i is the positioning times; Δ dn1,iThe difference value between the measured distance of the base station and the measured distance of the clock reference base station is obtained when the nth base station and the clock reference base station are positioned for the ith time; c is the UWB signal transmission speed; Δ tiTDOA value for the ith location;
Figure BDA0002818464100000091
the local arrival time of the positioning signal corrected by the nth base station is obtained; t is t1,iThe local arrival time of the positioning signal of the clock reference base station;
equation (5) is set as the observation vector:
h(si)＝[Δd21,i,Δd31,i,Δd41,i] (6)
in the formula,. DELTA.d21,i、Δd31,i、Δd41,iRespectively, the difference between the measured distance of the base stations 2, 3, 4 and the measured distance of the base station 1.
Unlike EKF, the UKF does not need to compute the jacobian matrix every time to keep statistics consistent with the absence of trace (UT) changes. Firstly, initialization is carried out:
Figure BDA0002818464100000092
2n +1 Sigma points, i.e., sampling points, are obtained by UT transform of equation (8), where n is 6.
Figure BDA0002818464100000093
In the formula, the upper label is the number of sampling points,
Figure BDA0002818464100000094
Figure BDA0002818464100000095
denotes the j-th column of the square root of the matrix, λ ═ a2And (n + k) -n is a scaling parameter used for reducing the total prediction error, the selection of a controls the distribution state of sampling, k is a parameter to be selected (ensuring that a matrix (n + lambda) P is a semi-positive definite matrix), and beta is more than or equal to 0 and is a weight coefficient to be selected, so as to merge high-order terms in the equation. The corresponding weight can be obtained from equation (9):
Figure BDA0002818464100000096
wherein m is the mean and c is the covariance.
Predict Sigma points:
Figure BDA0002818464100000101
and F is a state transition matrix and is obtained through a system motion model.
And multiplying and summing the one-step prediction of the Sigma point and the corresponding weight to obtain a one-step prediction value and a corresponding prediction covariance of the system state after propagation.
Figure BDA0002818464100000102
And (3) updating the observation of the UKF, generating a one-step prediction according to the formula (11), generating new Sigma points by repeated formulas (8) and (9), inputting the new Sigma points into an observation equation, obtaining a prediction observation value, and obtaining a mean value and a covariance of system prediction by repeated formulas (10) and (11).
Figure BDA0002818464100000103
Wherein
Figure BDA0002818464100000104
Is an observation equation and is a nonlinear equation.
And calculating a Kalman gain matrix.
Figure BDA0002818464100000105
The state and covariance of the system are updated.
Figure BDA0002818464100000106
Figure BDA0002818464100000107
Equation (14) is the predicted state required by the robot, where (x)i+1,yi+1,zi+1) Is the estimated coordinate point of the robot.
Step S6: and (5) the clock reference base station repeatedly executes the steps 3 to 5 by taking the interval period of the synchronous signal as an interval and the interval period of the positioning signal as an interval, and the coordinates of the mobile tag are obtained in real time until the positioning is stopped.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims (4)

1. An indoor robot positioning method based on UWB is characterized by comprising the following steps:
step 1: constructing an indoor positioning system, arranging at least four base stations and a mobile tag attached to a robot, wherein the robot takes the mobile tag as a coordinate point of the robot;
step 2: taking any one of all base stations as a clock reference base station, when the base station acquires a first positioning signal sent by a robot, accumulating and timing all the base stations from zero, recording the accumulated timing as the working time of the base station, and when the base station receives the signal, taking the working time of the current base station as the local arrival time of the signal;
and step 3: the clock reference base station transmits synchronous signals to other base stations, and the other base stations establish a clock model by utilizing an interpolation synchronization algorithm based on the local time and the synchronous times of the synchronous signals;
the robot transmits positioning signals to all base stations, and the base stations except the clock reference base station extrapolate the clock offset of the positioning signals based on the local arrival time of the positioning signals, the positioning times and the clock model;
the base stations except the clock reference base station carry out clock offset correction on the local arrival time of the positioning signal by subtracting the clock offset of the positioning signal from the local arrival time of the positioning signal;
and 4, step 4: the base station sends the local arrival time of the positioning signal corrected in the step 3 to the robot, and the robot subtracts the local arrival time of the positioning signal sent by the time reference base station from the local arrival time of the corrected positioning signal sent by the base stations except the time reference base station one by one to obtain a plurality of TDOA values;
and 5: establishing a motion model of the robot, and acquiring mobile tag coordinates by using a UKF (unscented Kalman Filter) algorithm based on a plurality of TDOA (time difference of arrival) values;
step 6: and (5) accumulating the synchronization times and the positioning times, repeatedly executing the steps 3 to 5 by the clock reference base station by taking the interval period of the synchronization signal as an interval and the positioning signal interval period of the robot by taking the interval period of the positioning signal as an interval, and acquiring the coordinates of the mobile tag in real time until the positioning is stopped.
2. The UWB-based indoor robot positioning method according to claim 1, wherein the other base station in step 3 establishes a clock model based on the local arrival time of the synchronization signal and the synchronization signal by using an interpolation synchronization algorithm, specifically:
Figure FDA0002818464090000021
wherein n is a base station serial number; k is the number of synchronization times; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tsn,kThe local arrival time of a synchronizing signal is the nth base station when the kth synchronization is carried out; epsilonn,kFor a total period of k times the synchronization signal is transmitted,
Figure FDA0002818464090000022
τncommunication propagation delay for base station n; rhosn,kThe nth base station is the nth base station, and the clock drift rate is obtained during the k-th synchronization; f. ofsSpacing frequencies for synchronization signals; Δ tn,k-1The total clock offset of the local arrival time of the synchronous signal at the k-1 synchronization time of the nth base station in the previous time.
3. The UWB-based indoor robot positioning method of claim 2, wherein in the step 3, the clock offset of the base station extrapolating the positioning signal based on the positioning signal and the clock model is specifically formulated as:
ρn,i＝Δtn,k+ρsn,k(tn,i-tsn,k)
wherein n is a base station serial number; k is the number of synchronization times; i is the positioning times; rhon,iClock skew of extrapolated positioning signal of local arrival time of positioning signal at ith positioning for base station n; Δ tn,kThe total clock offset of the local arrival time of the synchronizing signal at the kth synchronization time of the nth base station; t is tn,iThe total clock offset of the local arrival time of the positioning signal at the ith positioning time is the nth base station; t is tsn,kFor the nth base station, the local arrival time of the synchronization signal is synchronized at the kth time.
4. The UWB-based indoor robot positioning method of claim 3, wherein in the step 5, in acquiring the coordinates of the mobile tag using the UKF filtering algorithm based on the plurality of TDOA values, a distance difference formula for acquiring a coordinate solution is:
Figure FDA0002818464090000031
wherein n is a base station serial number; i is the positioning times; Δ dn1,iThe difference value between the measured distance of the base station and the measured distance of the clock reference base station is obtained when the nth base station and the clock reference base station are positioned for the ith time; c is the UWB signal transmission speed; Δ tiTDOA value for the ith location;
Figure FDA0002818464090000032
the local arrival time of the positioning signal corrected by the nth base station is obtained; t is t1,iThe local arrival time of the positioning signal of the base station is referenced to the clock.
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CN114040327A (en) * 2021-11-25 2022-02-11 江苏科技大学 Construction method of space visual benchmarking system based on UWB
CN114125706A (en) * 2021-11-24 2022-03-01 合肥朗云物联科技股份有限公司 UWB-based forklift arrival reminding display system
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