CN114245301B - UWB underground target positioning method based on redundant distance - Google Patents
UWB underground target positioning method based on redundant distance Download PDFInfo
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Abstract
The invention discloses a UWB underground target positioning method based on redundant distance. The method comprises the following steps: collecting the distance between a group of positioning labels and four different positioning base stations through a UWB base station; obtaining a coordinate initial value through a least square method by using three ranging distances; judging whether three initial coordinate values are obtained, and if the conditions are met, optimizing the three initial coordinate positions by using a particle swarm optimization algorithm to obtain a final coordinate; otherwise, the distance between the positioning label and the positioning base station is obtained continuously through the positioning base station, and then a new set of initial coordinate values are obtained by adopting a least square method. The advantages are that: according to the invention, the particle swarm algorithm is utilized to optimize the initial values of a plurality of groups of coordinates, so that the positioning accuracy can be effectively improved.
Description
Technical Field
The invention belongs to the technical field of underground positioning, and particularly relates to an Ultra Wide Band (UWB) underground target positioning method based on a redundant distance.
Background
In recent years, the demand of China for coal is more and more urgent, a large number of workers are required to participate in underground mining operation, but safety accidents are easy to occur due to limited underground space and severe environment. When an accident occurs, the rescue workers need to determine the accurate position of the accident workers first to drive away the rescue, so that an accurate positioning system is needed to provide position information for underground workers.
The currently used positioning technology mainly comprises WIFI positioning, zigbee positioning, UWB positioning and the like. The WIFI-based positioning method utilizes an RSSI positioning principle, transmits wireless signals to the outside through a base station, and calculates the distance between a positioning tag and the positioning base station according to the signal intensity. The method has the advantages of simple deployment, low cost and easy realization. But the positioning accuracy is not high, the underground environment is bad, and the influence of external factors on the signal intensity is large.
The positioning method based on Zigbee is based on the principle that the Zigbee networks are communicated with each other, and each module in each network can position or monitor the target, so that the aim of positioning is fulfilled. Its advantages are high anti-interference power, high transmission speed and high expandability.
Based on the UWB positioning method, also called ultra wideband communication, information is obtained by propagation of electromagnetic waves. The main practical positioning methods are TOA and TDOA.
The TOA method is a method of determining a target position based on signal arrival time. Firstly, the transmission time from the positioning tag to the electromagnetic wave of the base station is obtained, and then the distance is obtained by multiplying the transmission speed of the electromagnetic wave. And then repeatedly acquiring the distance data of at least three groups of different base stations, and obtaining the position coordinates through algorithms such as LS and the like.
The TDOA method is a way to determine the target location based on the difference in propagation time between a positioning tag and a plurality of positioning base stations. The method is an improvement of the TOA method, is not influenced by time synchronization, and has higher positioning accuracy.
Chinese patent application No. 201911068319.7 discloses an outdoor target positioning method based on BP neural network and TDOA. Although the invention improves the positioning accuracy, the training time is too long and the time cost is high.
Disclosure of Invention
The invention aims to provide a UWB underground positioning method based on a redundant distance, which improves the positioning precision under the influence of a ranging error so as to enable a positioning system to have higher practicability and accuracy.
Aiming at the problem of errors influenced by environmental factors in the UWB ranging process, the method determines a plurality of groups of position initial values by measuring a plurality of groups of distance values, and then obtains final accurate positioning by using a particle swarm optimization method.
The method comprises the following specific implementation steps:
step (1), collecting the distance between a positioning base station and a positioning label;
step (2), calculating an initial theoretical value of the positioning label by using a least square method according to the error-containing distance di in the step (1);
step (3), repeating the steps (1) - (2) to obtain initial theoretical values of a plurality of groups of positioning labels; then judging whether the initial theoretical value of each group of positioning labels generates three values or not; if the requirements are not met, returning to the step (1); and if the requirements are met, optimizing the three numerical values by using a particle swarm optimization method to obtain the final coordinates of the underground target.
It is a further object of the present invention to provide a computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the above-mentioned method.
It is a further object of the present invention to provide a computing device comprising a memory having executable code stored therein and a processor which, when executing the executable code, implements the method described above.
Compared with the prior art, the invention has the following advantages:
first, the invention is a new locating method idea provided on the basis of the original hardware equipment, and no additional hardware equipment is needed.
Secondly, according to the invention, aiming at the angle of errors in ranging, initial positioning is obtained by obtaining a plurality of groups of redundant distances with errors, and finally a final positioning label is obtained by utilizing an optimization algorithm, so that the positioning precision can be remarkably improved.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a simulation diagram of a positioning base station and a positioning tag.
FIG. 3 is a simulation diagram of locating a locating tag with a measurement target.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, the implementation steps of the present invention are as follows:
step 1, acquiring the distance between a positioning base station and a positioning label; the method specifically comprises the following steps:
1-1, because the initial coordinates can be obtained by using a least square method as long as the distances between more than three different positioning base stations and the positioning tag are obtained, four positioning base stations are randomly selected; the TW-TOF ranging method is utilized to obtain the measurement distances between four positioning base stations and the positioning tag, and the measurement distances are specifically shown in a formula (1):
wherein s is i Representing a distance measurement value T of a positioning ith base station and a positioning tag 0i Time for transmitting signal with request property to ith base station for positioning tag, T 1i Time T for the ith positioning base station to receive signals sent by the positioning tag 2i For the response signal time, T, sent by the ith positioning base station to the positioning tag 3i And C is the speed of light when the response signal sent by the ith positioning base station is received by the positioning tag.
1-2 due to influence of various factors such as environment, the distance measurement value s is obtained i An error is necessarily present; therefore, the distance formula containing the error is as follows:
d i ＝s i +w formula (2)
Wherein d is i Distance value s representing noise-containing error measured by ith base station i The true distance between the ith base station and the positioning tag is represented, and w represents the error value.
In order to restore the real environment conveniently, a noise error function is set, and the function formula is as follows:
wherein w is an error value, θ is a ranging error of UWB, δ is a standard deviation, obeys a normal distribution with a mean value of 0 and a standard deviation of 0.2.
Step 2, according to step 1, the distance d containing error i Calculating an initial theoretical value of the positioning label by using a least square method; the method specifically comprises the following steps:
2-1, constructing the relation between the distance containing the error and the positioning base station and the positioning label:
where (x, y) represents the initial theoretical value of the positioning tag, (x) i 、y i ) Representing the coordinates of the ith positioning base station. d, d i Is the distance of the ith base station from the locating tag. Four sets of distance equations (4) can be obtained from the distance sets obtained at the four base stations.
2-2 establishing a following matrix relation formula based on the formula (4) to obtain an initial theoretical value of a group of positioning labels;
i.e. ax=b.
Wherein,
and step 3, repeating the step 1-2 to obtain initial theoretical values of a plurality of groups of positioning labels.
Judging whether the initial theoretical value of each group of positioning labels generates three values or not; if the requirements are not met, returning to the step 1; and if the requirements are met, optimizing the three numerical values by using a particle swarm optimization method to obtain the final coordinates of the underground target.
The method is based on the redundant measurement distance to acquire the final position, and if more initial positions are acquired, the accuracy of the result is increased, but the time waste caused by repeated measurement is also brought. Therefore, considering the time overhead, the three initial positions can be acquired, so that the improvement of the position accuracy can be ensured, and the waste of time resources can be avoided.
The particle swarm optimization method specifically comprises the following steps:
v i ＝ωv i +c 1 r 1 (p besti -q i )+c 2 r 2 (p besti -q i )
q i ＝q i +v i
wherein v is i Is the ith particle velocity, w is the inertiaSex weight coefficient, c 1 、c 2 Is the acceleration coefficient, r 1 、r 2 Is two random numbers, p besti Represents the individual optimal position, g, of the ith particle compared to the measured position tag besti Indicating the global optimum of the current population of particles relative to the measured position tags. q i Indicating the current particle position.
Fitness represents the average value of the distances between the current particle and the initial theoretical value, and the value is:
since there are 3 initial coordinates in total, the value of N is 3, which represents the number of initial coordinate values, (a, b) represents the current particle coordinates, (m) i ,n i) The i-th initial theoretical value of the positioning tag is represented, i=0, 1,2.
The effects of the present invention are further described below in conjunction with the simulation diagrams of fig. 2 and 3.
Fig. 2 is a simulation diagram of a positioning base station and a real positioning tag. The abscissa in fig. 2 represents the current position of an object, "+" represents the coordinates of a real positioning tag, and the circle represents the position coordinates of a positioning base station. The coordinates of the positioning tag are (15, 15), and the coordinates of the four positioning base stations are respectively: (10, 5), (25,7), (15, 25) and (25, 20).
FIG. 3 is a simulation diagram of the positioning of a positioning tag and a measurement target. The three initial coordinate positions calculated by the least square method are (15.99791744,15.04727496) (15.6535353,14.68278183) and (14.52301114,15.39633227), respectively. The distance difference from the true target location of the locating tag is 0.999,0.726 and 0.62.
The final positioning label position obtained after the three initial coordinates are optimized by utilizing the particle swarm is 15.394244,15.0441228, and the distance difference between the final positioning label position and the real target position of the positioning label is 0.3967.
The accuracy of target positioning is obviously optimized through the comparison of coordinates before and after particle swarm optimization.
The simulation experiment shows that: the method has the feasibility and can effectively improve the positioning accuracy in the environment with noise errors, and is a very practical and efficient underground positioning method.
The above embodiments are not intended to limit the present invention, and the present invention is not limited to the above embodiments, and falls within the scope of the present invention as long as the present invention meets the requirements.
Claims (4)
1. The UWB underground target positioning method based on the redundant distance is characterized by comprising the following steps of:
step (1), collecting the distance between a positioning base station and a positioning label; the method specifically comprises the following steps:
1-1 randomly selecting four positioning base stations, and acquiring the measurement distances between the four positioning base stations and a positioning tag by using a TW-TOF ranging method:
wherein s is i Representing a distance measurement value T of a positioning ith base station and a positioning tag 0i Time for transmitting signal with request property to ith base station for positioning tag, T 1i Time T for the ith positioning base station to receive signals sent by the positioning tag 2i For the response signal time, T, sent by the ith positioning base station to the positioning tag 3i The response signal time sent by the ith positioning base station is received for the positioning tag, and C is the light speed;
1-2 based on distance measurement s i Obtaining the distance containing errors:
d i ＝s i +w formula (2)
Wherein d is i A distance value representing a noise-containing error measured by the i-th base station, w representing the noise error;
step (2), the distance d containing error according to the step (1) i Calculating an initial theoretical value of the positioning label by using a least square method; the method specifically comprises the following steps:
2-1, constructing the relation between the distance containing the error and the positioning base station and the positioning label:
where (x, y) represents the initial theoretical value of the positioning tag, (x) i ，y i ) Representing the coordinates of the ith positioning base station;
2-2 establishing a following matrix relation formula based on the formula (4) to obtain an initial theoretical value of a group of positioning labels;
wherein the method comprises the steps of
Step (3), repeating the steps (1) - (2) to obtain initial theoretical values of a plurality of groups of positioning labels; then judging whether the initial theoretical value of each group of positioning labels generates three values or not; if the requirements are not met, returning to the step (1); if the requirements are met, optimizing the three numerical values by using a particle swarm optimization method to obtain the final coordinates of the underground target;
the particle swarm optimization method specifically comprises the following steps:
v i ＝ωv i +c 1 r 1 (p besti -q i )+c 2 r 2 (g besti -q i ) Formula (5)
q i ＝q i +v i Formula (6)
Wherein v is i Is the ith particle velocity, w is the inertial weight coefficient, c 1 、c 2 Is the acceleration coefficient, r 1 、r 2 Is two random numbers, p besti Represents the individual optimal position, g, of the ith particle compared to the measured position tag besti Representing the current population of particles relative toGlobal optimal position of the measured positioning tag; q i Indicating the current particle position.
2. A redundant distance based UWB down-hole target location method of claim 1 wherein the noise error function:
wherein θ is the ranging error of UWB, δ is the standard deviation, obeying the normal distribution with the mean value of 0 and standard deviation of 0.2.
3. A computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of claim 1 or 2.
4. A computing device comprising a memory having executable code stored therein and a processor which, when executing the executable code, implements the method of claim 1 or 2.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108168556A (en) * | 2018-01-11 | 2018-06-15 | 中国矿业大学 | Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions |
| CN111948602A (en) * | 2020-08-17 | 2020-11-17 | 南京工程学院 | Two-dimensional UWB indoor positioning method based on improved Taylor series |
| CN113777557A (en) * | 2021-09-26 | 2021-12-10 | 北方工业大学 | UWB indoor positioning method and system based on redundant distance screening |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108168556A (en) * | 2018-01-11 | 2018-06-15 | 中国矿业大学 | Merge particle group optimizing and the driving support frame ultra wide band location method of Taylor series expansions |
| CN111948602A (en) * | 2020-08-17 | 2020-11-17 | 南京工程学院 | Two-dimensional UWB indoor positioning method based on improved Taylor series |
| CN113777557A (en) * | 2021-09-26 | 2021-12-10 | 北方工业大学 | UWB indoor positioning method and system based on redundant distance screening |
Non-Patent Citations (1)
| Title |
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| 非视距环境下的超宽带室内定位算法;江歌;李志华;;计算机测量与控制(第11期);全文 * |
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