CN113567925A - Ultra-wideband technology-based accurate positioning method, system and device - Google Patents
Ultra-wideband technology-based accurate positioning method, system and device Download PDFInfo
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Abstract
The invention provides a method, a system and a device for accurate positioning based on an ultra-wideband technology, wherein the method comprises the following steps: acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station; obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm; obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series; taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate; obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm; and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
Description
Technical Field
The invention belongs to the field of ultra-wideband technology positioning, and particularly relates to a method for combining a CTK algorithm and a least mean square algorithm based on a signal arrival time difference principle.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the continuous progress of science and technology, accurate indoor positioning technology has become a main technical problem and a hotspot in the research field of the application fields of mobile communication and other information electronic technologies in China at present. Currently, the widely used positioning detection technologies include a GPS technology, a wireless technology, a bluetooth technology, a ZigBee technology, and the like. However, the above positioning method is relatively suitable for an outdoor open environment, in a non-line-of-sight environment, obstacles such as walls and home appliances may interfere with signal transmission, especially in indoor places such as large department stores and indoor gymnasiums, ultra-wideband signals may be shielded and reflected by equipment, and physical characteristics of signal propagation may be lost. The above manner makes it difficult to achieve accurate positioning.
The ultra-wideband (UWB) technology has short wireless communication distance, can realize high-speed wireless communication, and has very low power consumption and low application resources in the communication process, so that the overall performance and the cost performance are high. The ultra-wideband positioning technology can greatly improve the positioning performance of the indoor navigation positioning system.
Currently, the calculation methods of the ultra-wideband Signal positioning technology mainly include four types, namely, an Angle of Arrival (AOA) based method, a Received Signal Strength Indication (RSSI) based method, a Time of Arrival (TOA) based method, and a Time Difference of Arrival (TDOA) based method. The present invention focuses on the TOA and TDOA methods. The RSSI positioning algorithm is mainly based on the distance between the tag and the base station, which has a certain strong and weak positive correlation with the received signal, and this positioning method is sensitive to the channel transmission characteristics, so that the channel characteristics must be clearly known. The AOA positioning algorithm is not suitable for use in indoor complex environments because it relies on electromagnetic wave transmission of wireless communication, is affected by multipath effects generated during transmission, and the same signal arrives at the base station at different angles, which greatly reduces the accuracy of position determination. The TOA positioning analysis algorithm requires that the tag and the base station have consistent standard reference positioning time, and the accuracy and the synchronism of the positioning time are very high, so that the method is difficult to realize in actual measurement. The TDOA positioning algorithm does not require that the label and the base stations have the same reference time, only a common reference clock is provided between the base stations, so that the difficulty of actual measurement is reduced, and the accuracy of the indoor positioning point can be effectively improved.
At present, the flow of a positioning algorithm which is widely applied is a CTK joint positioning algorithm, but the algorithm only utilizes a single Kalman filtering algorithm to carry out filtering processing, and the positioning effect does not meet the expected high-precision positioning requirement.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method, a system and a device for accurate positioning based on the ultra-wideband technology, wherein the method, the system and the device have an error in a range of 0.04m in a static positioning test, and a data error of ninety percent of dynamic positioning is about 0.07 m.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a precise positioning method based on ultra-wideband technology.
An accurate positioning method based on ultra-wideband technology comprises the following steps:
acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm;
obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series;
taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate;
obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm;
and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
A second aspect of the invention provides a precision positioning system based on ultra-wideband technology.
An accurate positioning system based on ultra-wideband technology, comprising:
an acquisition module configured to: acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
a motion trajectory generation module configured to: obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm; obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series; taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate; obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm; and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
The third aspect of the invention provides a precise positioning method based on the ultra-wideband technology.
An accurate positioning method based on ultra-wideband technology comprises the following steps:
the ultra-wide band tag arranged on the positioned object transmits an ultra-wide band signal carrying the ultra-wide band tag;
at least four detection base stations fixed on the same horizontal plane receive the ultra-wide band signals transmitted by the ultra-wide band tag;
the detection base station generates a distance signal between the ultra-wide band tag and the detection base station when the ultra-wide band signal is received by the detection base station and transmits the distance signal to the cloud server;
the cloud server calculates an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and a detection base station by adopting a Chan algorithm, and then calculates the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
Furthermore, the detection base station and the ultra-wideband tag are powered by a mobile power supply.
Furthermore, the ultra-wide band tag and the detection base station as well as the detection base station and the cloud server are connected in a wireless communication mode.
A fourth aspect of the invention provides a precision positioning device based on ultra-wideband technology.
The utility model provides an accurate positioner based on ultra wide band technique, is including locating the ultra wide band label on the object of being fixed a position, fixing four at least detection basic stations and cloud ware on same horizontal plane:
the ultra-wideband tag is used for transmitting an ultra-wideband signal carrying the ultra-wideband tag;
the detection base station is used for receiving the ultra-wideband signal transmitted by the ultra-wideband tag, generating a distance signal between the ultra-wideband tag and the detection base station when the ultra-wideband signal is received by the detection base station, and transmitting the distance signal to the cloud server;
the cloud server is used for calculating an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and the detection base station by adopting a Chan algorithm, and then calculating the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
Furthermore, the ultra-wideband detection device further comprises a mobile power supply, and the detection base station and the ultra-wideband tag are powered by the mobile power supply.
Furthermore, the ultra-wide band tag and the detection base station as well as the detection base station and the cloud server are connected in a wireless communication mode.
A fifth aspect of the invention provides a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for ultra-wideband technology based fine positioning as defined in the first aspect above.
A sixth aspect of the invention provides a computer apparatus.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the ultra wideband technology based fine positioning method according to the first aspect when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
based on the TDOA method, the invention optimizes the label tracking and positioning algorithm, constructs an indoor positioning system with high positioning precision, multipath fading resistance and easy digitization, and meets the requirement of high-precision positioning.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a flow chart of a method of precision positioning based on ultra-wideband technology;
FIG. 2 is a comparison graph of a CTK algorithm and a joint algorithm position estimation curve;
FIG. 3 is a comparison graph of the mean square error curves of the CTK algorithm and the joint algorithm;
FIG. 4 is a diagram of an experimental environment;
FIG. 5 is a comparison graph of tag positions of the CTK algorithm and the improved algorithm in a static experiment;
FIG. 6 is a graph of tag position estimation error of the CTK algorithm and the improved algorithm in a static experiment;
FIG. 7 is a diagram of a motion trajectory of a trolley obtained by an improved algorithm in a dynamic experiment;
FIG. 8 is a graph of the movement position of the dolly in the dynamic experiment;
fig. 9 is a diagram of estimated coordinates of the motion position of the trolley obtained by the improved algorithm in the dynamic experiment.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
It is noted that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of the present disclosure. It should be noted that each block in the flowchart or block diagrams may represent a module, a segment, or a portion of code, which may comprise one or more executable instructions for implementing the logical function specified in the respective embodiment. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Example one
As shown in fig. 1, the present embodiment provides an accurate positioning method based on ultra wideband technology, and the present embodiment is illustrated by applying the method to a server, it is understood that the method may also be applied to a terminal, and may also be applied to a system including a terminal and a server, and implemented by interaction between the terminal and the server. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network server, cloud communication, middleware service, a domain name service, a security service CDN, a big data and artificial intelligence platform, and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the application is not limited herein. In this embodiment, the method includes the steps of:
acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm;
obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series;
taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate;
obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm;
and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
The specific embodiment employed is as follows:
the Taylor series expansion method is a gradual recursion algorithm. The label coordinate information obtained by solving the algorithm has high precision, but the algorithm has large calculation amount and is suitable for various channel environments. The principle of the algorithm is to substitute the previous calculation result as a known value into the subsequent calculation, and take the estimated coordinates of the label as the initial iteration value. However, this algorithm cannot guarantee convergence when the initial iteration value is not close to the actual value. In order to make the initial iteration value more accurate, a combination of the Chan's algorithm and the Taylor series algorithm is adopted to locate the tags. Firstly, a label estimation value obtained by a Chan's algorithm is used as an initial iteration value of a Taylor series, and then the label is positioned by using a Taylor series expansion algorithm.
2. Taking the tag coordinate estimation value obtained by the C-T joint positioning algorithm as the optimal estimation value of the last moment in the Kalman filtering algorithm to carry out preliminary estimation on the tag positioning result, wherein the estimation value is defined as follows:
Xk＝FkXk-1+Bkuk
Xk＝Xk+K(Zk-HkXk)
wherein, XkAn estimated value, X, representing a state variable at the current timek-1Representing the optimum estimate of the state variable at the previous moment, FkIs a state change matrix, ZkAnd K is a Kalman gain matrix for the measurement value at the current moment.
3. Based on the principles of wiener filtering and the fastest descent method, a Least Mean Square (LMS) algorithm which does not need to know the mathematical statistical characteristics of a current input signal and a current expected signal is provided, and the weighting factor of the current time is equal to the sum of the proportional term of a negative mean square error gradient and the weighting factor of the previous time. The algorithm has low complexity and relatively good convergence for calculation under a stable signal condition. Which requires that the error of the filter between the actual desired output value and the response value complies with the Minimum Mean Square Error (MMSE) criterion. After the initial estimation of the label coordinate is obtained by utilizing the CTK joint positioning algorithm, the estimation value is used as the input value of a minimum mean square filter, the data generated by simulation is used as the expected value, the label coordinate is secondarily estimated, and the mean square error between the expected value and the estimation value is further reduced. The expression is defined as follows:
let the output signal of the filter be:
y(n)＝wT(n)x(n)
the error signals are:
e(n)＝d(n)-y(n)
the widely used adaptive algorithm is a 'descent' algorithm, and the gradient vector of the mean square error is used as an updating vector in the reverse direction to obtain a weight updating expression as follows:
w(n)＝w(n-1)+μ(n)e(n)x(n)
in the above formula, w (n) is the weight vector of the nth iteration, μ (n) is the update step of the nth iteration,
4. in the simulation process, a group of random numbers generated by MATLAB is used as expected values, the CTK algorithm and the combined positioning algorithm combined with the least mean square algorithm are used for respectively positioning, the track obtained by positioning is compared with the real track, the target node track of the improved positioning algorithm can be obtained by performing mean square error analysis, the target node track is closer to the real track, and the error value is obviously reduced. The data set acquired by the DWM1000 module is used as experimental data and is subjected to simulation analysis, and experimental results show that the error of the positioning algorithm before improvement is within 0.1m in a static positioning test, and the error of the positioning algorithm after improvement is within 0.04m, so that the positioning accuracy of the system is greatly improved.
Example two
The embodiment provides an accurate positioning system based on ultra-wideband technology.
An accurate positioning system based on ultra-wideband technology, comprising:
an acquisition module configured to: acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
a motion trajectory generation module configured to: obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm; obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series; taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate; obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm; and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
EXAMPLE III
The embodiment provides an accurate positioning method based on an ultra-wideband technology.
An accurate positioning method based on ultra-wideband technology comprises the following steps:
the ultra-wide band tag arranged on the positioned object transmits an ultra-wide band signal carrying the ultra-wide band tag;
at least four detection base stations fixed on the same horizontal plane receive the ultra-wide band signals transmitted by the ultra-wide band tag;
the detection base station generates a distance signal between the ultra-wide band tag and the detection base station when the ultra-wide band signal is received by the detection base station and transmits the distance signal to the cloud server;
the cloud server calculates an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and a detection base station by adopting a Chan algorithm, and then calculates the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
The kalman filter algorithm and its derivatives can only be implemented if the observed noise in the positioning system and the noise it generates throughout are known and constant. However, in practice, the noise of the system varies with time, and the noise interference covariance of the system cannot be regarded as constant. Therefore, in the simulation test analysis before the experiment, the Sage-Husa adaptive filtering algorithm is used to improve the traditional Kalman filtering algorithm, so that the assumption is more real, and the algorithm calculation steps are as follows:
(1) a prediction stage:
xk＝Ak-1xk-1+Bk-1uk-1
Pk＝Ak-1Pk-1AT k-1+Qk-1
(2) and (3) an updating stage:
ek＝yk-Hkxk+Dkuk
Rk＝(1-bk)Rk-1+bkekek T-HkPkHk T
(3) and (3) error covariance updating:
Kk＝PkHk T(HkPkHk T+Rk)-1
xk＝xk+dkek
Pk＝(1-KkHk)Pk
(4) statistical properties of process noise:
Qk＝(1-dk)Qk-1+(Kkekek TKk T+Pk-Ak-1Pk-1AT k-1)
wherein, XkIndicating the state estimate at time k, Xk-1Optimal estimation of state representing time k-1Evaluation of value, PkIs the error covariance matrix at time k, FkIs a state change matrix, K is a gain matrix of Kalman filtering, QkIs the covariance matrix, R, of the system process noisekIs a covariance matrix of the measured noise.
In this embodiment, under the condition that the coordinate value of the initial motion position of the tag is (30, 40), a group of random values is generated by using MATLAB to obtain the real trajectory of the target motion, and a trajectory comparison graph and a mean square error comparison graph of the position of the target node obtained by using the C-T algorithm in combination with the Sage-Husa adaptive filtering algorithm and estimating the position of the tag to be detected and the improved algorithm are shown in fig. 2 and 3.
Example four
The embodiment provides a precise positioning device based on ultra-wideband technology.
The utility model provides an accurate positioner based on ultra wide band technique, is including locating the ultra wide band label on the object of being fixed a position, fixing four at least detection basic stations and cloud ware on same horizontal plane:
the ultra-wideband tag is used for transmitting an ultra-wideband signal carrying the ultra-wideband tag;
the detection base station is used for receiving the ultra-wideband signal transmitted by the ultra-wideband tag, generating a distance signal between the ultra-wideband tag and the detection base station when the ultra-wideband signal is received by the detection base station, and transmitting the distance signal to the cloud server;
the cloud server is used for calculating an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and the detection base station by adopting a Chan algorithm, and then calculating the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
The present embodiment employs a DWM1000 module as an ultra-wideband signal transmitter. Hardware part of the experiment: 1 label, 1 intelligent car, 4 location base stations, 1 notebook computer, 4 portable power source. And the base station is connected with a computer and used for acquiring data and processing the data, and the base station and the label are powered by a mobile power supply. The size of the experimental environment is 5m multiplied by 5m, the base station is placed at four corners of the intelligent car track, and the tags are placed on the intelligent car to move, as shown in fig. 4.
2. Analyzing the positioning test result of the static system:
a label is placed in the test environment with real coordinates (99, 53) in cm. And analyzing the static positioning result of the label position in the experiment by adopting a CTK algorithm, a CTK algorithm and a least mean square algorithm double-positioning algorithm by using MATLAB, as shown in FIG. 5. In the figure, the straight connecting lines represent the connecting lines of the label positions estimated by the algorithm before improvement, and the star connecting lines represent the connecting lines of the label positions estimated by the algorithm after improvement. As can be seen from the graph, the target node position estimated by the algorithm before the improvement is more divergent, the target node position estimated by the algorithm after the improvement is closer to the real position value, and the aggregative property is better.
Fig. 6 shows a tag position error comparison graph obtained before and after the improvement, and it can be known from the graph that the estimation error of the algorithm before the improvement is within the range of 0.1m, and the estimation error of the algorithm after the improvement on the target node position is reduced to be within the range of 0.04m, which proves that the accuracy of the algorithm after the improvement on the estimation of the target node position is higher and the stability is better.
Analyzing the positioning test result of the dynamic system:
in the system dynamic experiment, the label is placed on the intelligent vehicle, the intelligent vehicle moves for a circle along the track, MATLAB is used for carrying out comparative analysis on the moving track line of the intelligent vehicle obtained by the algorithm before and after the improvement, as shown in figure 7, the star-shaped connecting line represents the track obtained by the algorithm after the improvement, and the straight-line connecting line represents the actually measured track of the vehicle. The deviation between the actually measured track and the track measured by the improved algorithm is maximum 0.1m, and the ninety percent data error is about 0.07m, as shown in fig. 8 and 9.
4. According to specific experimental analysis results, the CTK algorithm and the least mean square algorithm are combined, the static positioning error of the double positioning algorithm is within the range of 0.04m, the dynamic positioning ninety percent data error is about 0.07m, the improved algorithm is small in positioning error and high in precision, and the positioning performance of a positioning system can be greatly improved.
EXAMPLE five
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the ultra-wideband technology-based precision positioning method as described in the first embodiment above.
EXAMPLE six
The embodiment provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the processor implements the steps in the ultra-wideband technology-based precise positioning method according to the first embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An accurate positioning method based on ultra-wideband technology is characterized by comprising the following steps:
acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm;
obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series;
taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate;
obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm;
and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
2. An accurate positioning system based on ultra-wideband technology, comprising:
an acquisition module configured to: acquiring a distance signal between an ultra-wideband tag and a detection base station when the ultra-wideband signal is received by the carrying detection base station;
a motion trajectory generation module configured to: obtaining an ultra-wideband tag estimation value according to a distance signal between the ultra-wideband tag and a detection base station by adopting a Chan's algorithm; obtaining an ultra-wideband tag coordinate estimation value by taking the ultra-wideband tag estimation value as an initial iteration value of a Taylor series; taking the ultra-wideband tag coordinate estimation value as an optimal estimation value of the last moment in a Kalman filtering algorithm to preliminarily estimate a tag positioning result to obtain a preliminary estimation value of the ultra-wideband tag coordinate; obtaining a secondary estimation value of the ultra-wideband label coordinate corresponding to the primary estimation value of the ultra-wideband label coordinate by using a least mean square algorithm; and obtaining the motion trail of the object carrying the ultra-wide band label based on the secondary estimation value of the ultra-wide band label coordinate.
3. An accurate positioning method based on ultra-wideband technology is characterized by comprising the following steps:
the ultra-wide band tag arranged on the positioned object transmits an ultra-wide band signal carrying the ultra-wide band tag;
at least four detection base stations fixed on the same horizontal plane receive the ultra-wide band signals transmitted by the ultra-wide band tag;
the detection base station generates a distance signal between the ultra-wide band tag and the detection base station when the ultra-wide band signal is received by the detection base station and transmits the distance signal to the cloud server;
the cloud server calculates an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and a detection base station by adopting a Chan algorithm, and then calculates the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
4. The ultra-wideband technology-based precise positioning method according to claim 3, wherein the detection base station and the ultra-wideband tag are both powered by a mobile power supply.
5. The ultra-wideband technology-based precise positioning method as claimed in claim 3, wherein the ultra-wideband tag and the detection base station, and the detection base station and the cloud server are connected by wireless communication.
6. The utility model provides an accurate positioner based on ultra wide band technique which characterized in that, including locating the ultra wide band label on being fixed a position the object, fix four at least detection basic stations and cloud ware on same horizontal plane:
the ultra-wideband tag is used for transmitting an ultra-wideband signal carrying the ultra-wideband tag;
the detection base station is used for receiving the ultra-wideband signal transmitted by the ultra-wideband tag, generating a distance signal between the ultra-wideband tag and the detection base station when the ultra-wideband signal is received by the detection base station, and transmitting the distance signal to the cloud server;
the cloud server is used for calculating an ultra-wide band tag estimation value according to a distance signal between the ultra-wide band tag and the detection base station by adopting a Chan algorithm, and then calculating the ultra-wide band tag coordinate estimation value by adopting a Taylor series expansion method; and calculating a primary estimation value of the ultra-wide band tag coordinate by adopting a Sage-Husa adaptive filtering algorithm, finally obtaining a secondary estimation value of the ultra-wide band tag coordinate by utilizing a least mean square algorithm, and obtaining the motion track of the positioned object based on the secondary estimation value of the ultra-wide band tag coordinate.
7. The ultra-wideband technology based precision positioning device of claim 6, further comprising a mobile power supply, wherein the detection base station and the ultra-wideband tag are powered by the mobile power supply.
8. The ultra-wideband technology based precision positioning device of claim 6, wherein the ultra-wideband tag and the detection base station are connected through wireless communication, and the detection base station and the cloud server are connected through wireless communication.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the ultra-wideband technology based fine positioning method as claimed in claim 1.
10. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, carries out the steps of the ultra wideband technology based fine positioning method as claimed in claim 1.
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