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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base station
positioning
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robot
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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
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    • 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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Abstract

本发明公开了一种基于UWB的室内机器人定位方法，通过设置一个时钟基准基站，以该基站时间为准，在每次时间同步时，根据时钟基准基站对其他基站的时钟偏移进行计算，并在基站的时钟偏移基础上计算机器人和基站之间定位时的时间偏移，机器人在后续的与基站之间进行定位的过程中，根据获取的时间偏移进行时间上的修正。本发明为每个基站创建时钟模型实现了对定位信号本地到达时间的修正，提供了分散计算的方法，提高了定位的实时性；同样避免了现有技术TWR方法的本地到达时间修正中出现的占用信道时长的缺点，在节省能耗的同时，也为以后的扩展性能做铺垫。

Figure 202011412172

The invention discloses a UWB-based indoor robot positioning method. By setting a clock reference base station, the time of the base station is taken as the criterion, and the clock offset of other base stations is calculated according to the clock reference base station during each time synchronization, and The time offset between the robot and the base station is calculated based on the clock offset of the base station. During the subsequent positioning process between the robot and the base station, the time is corrected according to the obtained time offset. The invention creates a clock model for each base station to realize the correction of the local time of arrival of the positioning signal, provides a method for decentralized calculation, and improves the real-time performance of the positioning; also avoids the problem of the local time of arrival correction of the prior art TWR method. The shortcoming of occupying the channel duration not only saves energy consumption, but also lays the groundwork for future expansion performance.

Figure 202011412172

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)

1.一种基于UWB的室内机器人定位方法，其特征在于，包括如下步骤：1. an indoor robot positioning method based on UWB, is characterized in that, comprises the steps: 步骤1：构建室内定位系统，布置至少四个基站和一个依附于机器人上的移动标签，机器人以移动标签作为其自身的坐标点；Step 1: Build an indoor positioning system, arrange at least four base stations and a mobile tag attached to the robot, and the robot uses the mobile tag as its own coordinate point; 步骤2：将所有基站中的任一个基站作为时钟基准基站，当基站获取到机器人发送的第一个定位信号时，所有基站从零开始累加计时，记为基站工作时长，当基站接收到信号时，将当前基站工作时长作为该信号的本地到达时间；Step 2: Use any one of all the base stations as the clock reference base station. When the base station obtains the first positioning signal sent by the robot, all the base stations start accumulative timing from zero, which is recorded as the working time of the base station. When the base station receives the signal , taking the current base station working time as the local arrival time of the signal; 步骤3：时钟基准基站向其他基站发射同步信号，其他基站基于同步信号本地达到时间、同步次数利用插值同步算法建立时钟模型；Step 3: The clock reference base station transmits a synchronization signal to other base stations, and the other base stations use an interpolation synchronization algorithm to establish a clock model based on the local arrival time of the synchronization signal and the number of synchronization times; 机器人向所有基站发射定位信号，除时钟基准基站以外的基站基于定位信号本地到达时间、定位次数、时钟模型外推定位信号的时钟偏移；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 signal based on the local arrival time of the positioning signal, the number of positioning times, and the clock model; 除时钟基准基站以外的基站通过将定位信号本地到达时间减去定位信号的时钟偏移，对定位信号本地到达时间进行时钟偏移修正；The base stations other than the clock reference base station perform 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; 步骤4：基站将所述步骤3中修正后的定位信号本地到达时间发送给机器人，机器人逐一将除时间基准基站之外的基站发送的修正后的定位信号本地到达时间减去时间基准基站发送的定位信号本地到达时间，获得数个TDOA值；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 base station other than the time reference base station from the local time of arrival of the positioning signal sent by the time reference base station one by one. The local arrival time of the positioning signal is obtained, and several TDOA values are obtained; 步骤5：建立机器人的运动模型，基于数个TDOA值利用UKF滤波算法获取移动标签坐标；Step 5: establish a motion model of the robot, and use the UKF filtering algorithm to obtain the coordinates of the mobile tag based on several TDOA values; 步骤6：累加同步次数、定位次数，时钟基准基站以同步信号间隔周期为间隔、机器人以定位信号间隔周期为间隔重复执行步骤3～步骤5，实时获取移动标签坐标直至停止定位。Step 6: Accumulate the number of synchronizations and positioning times. The clock reference base station uses the synchronization signal interval period as an interval, and the robot repeats steps 3 to 5 at the interval of the positioning signal interval period, and obtains the coordinates of the mobile tag in real time until it stops positioning. 2.如权利要求1所述的基于UWB的室内机器人定位方法，其特征在于，所述步骤3中其他基站基于同步信号本地到达时间、同步信号利用插值同步算法建立时钟模型具体为：2. the indoor robot positioning method based on UWB as claimed in claim 1, is characterized in that, in described step 3, other base station utilizes interpolation synchronization algorithm to build clock model based on synchronous signal local time of arrival, synchronous signal and is specifically:
Figure FDA0002818464090000021
Figure FDA0002818464090000021
 其中，n为基站序号；k为同步次数；Δtn,k为第n号基站，第k次同步时同步信号本地到达时间的总时钟偏移量；tsn,k为第n号基站，第k次同步时同步信号本地到达时间；εn,k为同步信号发射k次的总周期，
Figure FDA0002818464090000022
τn为第n号基站的通信传播延迟；ρsn,k为第n号基站，第k次同步时时钟飘移率；fs为同步信号间隔频率；Δtn,k-1为前一次第n号基站，第k-1次同步时同步信号本地到达时间的总时钟偏移量。Among them, n is the base station serial number; k is the number of synchronizations; Δt n,k is the nth base station, the total clock offset of the local arrival time of the synchronization signal at the kth synchronization; t sn,k is the nth base station, the The local arrival time of the synchronization signal during k synchronizations; ε n,k is the total period of the synchronization signal transmitted k times,
Figure FDA0002818464090000022
τ n is the communication propagation delay of the nth base station; ρ sn,k is the nth base station, the clock drift rate during the kth synchronization; f s is the synchronization signal interval frequency; Δt n,k-1 is the previous nth time Base station No., the total clock offset of the local arrival time of the synchronization signal during the k-1th synchronization. 3.如权利要求2所述的基于UWB的室内机器人定位方法，其特征在于，所述步骤3中，基站基于定位信号、时钟模型外推定位信号的时钟偏移具体公式为：3. the indoor robot positioning method based on UWB as claimed in claim 2, is characterized in that, in described step 3, the clock offset concrete formula of base station extrapolation positioning signal based on positioning signal, clock model is: ρn,i＝Δtn,k+ρsn,k(tn,i-tsn,k)ρ n,i =Δt n,k +ρ sn,k (t n,i -t sn,k ) 其中，n为基站序号；k为同步次数；i为定位次数；ρn,i为第n号基站，第i次定位时定位信号本地到达时间的外推定位信号的时钟偏移；Δtn,k为第n号基站，第k次同步时同步信号本地到达时间的总时钟偏移量；tn,i为第n号基站，第i次定位时定位信号本地到达时间的总时钟偏移量；tsn,k为第n号基站，第k次同步时同步信号本地到达时间。Among them, n is the base station serial number; k is the synchronization times; i is the positioning times ; k is the nth base station, the total clock offset of the local arrival time of the synchronization signal in the kth synchronization; t n,i is the nth base station, the total clock offset of the local arrival time of the positioning signal in the ith positioning ; t sn,k is the nth base station, the local arrival time of the synchronization signal during the kth synchronization. 4.如权利要求3所述的基于UWB的室内机器人定位方法，其特征在于，所述步骤5中，在基于数个TDOA值利用UKF滤波算法获取移动标签坐标过程中，获取坐标解的距离差公式为：4. the indoor robot positioning method based on UWB as claimed in claim 3, is characterized in that, in described step 5, in utilizing UKF filter algorithm to obtain moving label coordinate process based on several TDOA values, obtain the distance difference of coordinate solution The formula is:
Figure FDA0002818464090000031
Figure FDA0002818464090000031
 其中，n为基站序号；i为定位次数；Δdn1,i为第n号基站和时钟基准基站在第i次定位时基站测量距离与时钟基准基站测量距离的差值；c为UWB信号传输速度；Δti为第i次定位的TDOA值；
Figure FDA0002818464090000032
为第n号基站修正后的定位信号本地到达时间；t1,i为时钟基准基站的定位信号本地到达时间。Among them, n is the base station serial number; i is the number of positioning times; Δd n1,i is the difference between the base station measurement distance and the clock reference base station measurement distance between the nth base station and the clock reference base station during the i-th positioning; c is the UWB signal transmission speed ; Δt i is the TDOA value of the i-th positioning;
Figure FDA0002818464090000032
is the local arrival time of the positioning signal after the correction of the nth base station; t 1,i is the local arrival time of the positioning signal of the clock reference base station.
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