CN110636436A - Three-dimensional UWB indoor positioning method based on improved CHAN algorithm - Google Patents

Three-dimensional UWB indoor positioning method based on improved CHAN algorithm Download PDF

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CN110636436A
CN110636436A CN201910789561.7A CN201910789561A CN110636436A CN 110636436 A CN110636436 A CN 110636436A CN 201910789561 A CN201910789561 A CN 201910789561A CN 110636436 A CN110636436 A CN 110636436A
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positioning
uwb
base stations
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detected
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陈利双
邬永强
李兆刚
章为昆
刘常涛
孙德春
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Zhejiang Wellsun Intelligent Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/0009—Transmission of position information to remote stations
    • G01S5/0018—Transmission from mobile station to base station
    • G01S5/0027—Transmission from mobile station to base station of actual mobile position, i.e. position determined on mobile
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/04—Position of source determined by a plurality of spaced direction-finders
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • 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
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination

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  • Remote Sensing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

The invention discloses a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm, which comprises the steps of receiving UWB positioning signals sent by a to-be-detected label carried by a to-be-detected object, and acquiring the arrival time parameters and the received signal strength parameters of UWB positioning signals received by each positioning base station; comparing the received signal strength parameters of each positioning base station, and arranging the received signal strength parameters in a descending order to obtain a second number of positioning base stations with the received signal strength parameters arranged in the front; respectively obtaining the arrival time parameters of a second number of positioning base stations, and determining each second positioning base stationThe distances from the positioning base stations to the labels to be detected are respectively counted; calculating the distance difference r between the tag to be detected and each of the second number of positioning base stations and the reference base stationif(ii) a And obtaining the distance difference, and obtaining the estimated position of the object to be measured based on a CHAN algorithm. The influence of non-line-of-sight errors is effectively reduced, the positioning precision is improved, and the accuracy of a positioning result is improved.

Description

Three-dimensional UWB indoor positioning method based on improved CHAN algorithm
Technical Field
The invention relates to the technical field of positioning and navigation, in particular to a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm.
Background
Ultra-wideband (UWB) positioning refers to using anchor nodes with known positions arranged in advance to communicate with newly added blind nodes, obtaining parameters related to distance, such as TOA (time of arrival), TDOA (time difference of arrival), AOA (angle of arrival), RSSI (received signal strength), etc., obtaining the distance from the parameters, and then obtaining the blind node position by adopting a corresponding positioning algorithm.
The CHAN algorithm is a positioning algorithm based on a TDOA model, and the method for Ultra Wide Band (UWB) positioning by utilizing the traditional CHAN algorithm is higher in positioning precision and more accurate in positioning result in a line-of-sight environment because the measurement error is smaller and the Gaussian distribution is obeyed. However, in a non-line-of-sight environment, the method for ultra-wideband (UWB) positioning using the conventional CHAN algorithm may cause a decrease in positioning accuracy and a less accurate positioning result due to the introduction of one or more non-line-of-sight errors.
Disclosure of Invention
The invention aims to provide a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm, and aims to solve the problems that due to the introduction of non-line-of-sight errors, the positioning accuracy is reduced, and the positioning result is inaccurate.
In order to achieve the above object, the present invention provides a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm, comprising:
under the environment of a first number of positioning base stations, receiving UWB positioning signals sent by a to-be-detected label carried by a to-be-detected object, and simultaneously acquiring the arrival time parameters and the received signal strength parameters of each positioning base station for receiving the UWB positioning signals;
according to the variation function of the received signal strength and the distance of the UWB positioning signals in the transmission process, comparing the received signal strength parameters of the UWB positioning signals received by each positioning base station, and arranging the received signal strength parameters in a descending order to obtain a second number of positioning base stations with the received signal strength parameters arranged in front;
respectively acquiring the arrival time parameters of the second number of positioning base stations for receiving the UWB positioning signals, and determining the distance from each second number of positioning base stations to the tag to be detected according to a first function;
calculating the distance difference r between the tag to be detected and each of the second number of positioning base stations and the reference base stationifWherein the reference base station f is one of a second number of positioning base stations;
obtaining the distance difference rifAnd obtaining the estimated position of the object to be detected based on the CHAN algorithm.
Preferably, the calculation method of the variation function is as follows:
Figure BDA0002179113560000021
wherein d is the distance between the positioning base station and the label to be detected, d0N is a path loss coefficient for the reference distance; chi shapeθIs a Gaussian random noise variable with mean 0 and variance δ, PL (d)0) For a distance of a label d to be measured0The reference strength of the signal.
Preferably, the first function is calculated in the following manner:
di＝c*ti；
wherein d isiThe distances from the second number of positioning base stations to the labels to be detected; t is tiTime of arrival at which said UWB location signals are received for a second number of location base stations; c is a constant.
Preferably, the obtaining of the distance difference and the obtaining of the estimated position of the object to be measured based on the CHAN algorithm include:
and determining the position estimation value of the object to be measured according to the second function and the third function.
Preferably, the position estimation value of the object to be measured is determined according to a second function and a third function, wherein the second function is calculated in a manner that:
rif＝ri-rf；
ri 2＝(rif+rf)2；
will r isi 2＝(rif+rf)2Unfolding:
2rifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz；
wherein the content of the first and second substances,
ki＝χi 2+yi 2+zi 2，kf＝χf 2+yf 2+zf 2，χif＝χi-χf，yif＝yi-yf，zif＝zi-zf；
the coordinates of the second positioning base stations are BSi (x)i，yi，zi)；riPositioning distances between the base stations and the labels to be detected for the second quantity; r isfIs the distance between the reference base station and the label to be measured;
introducing a measurement error:
rif＝rif 0+c(ti-tf)＝rif 0Δtif；
2r isifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz is written in matrix form:
θ＝h-GaZa；
wherein the content of the first and second substances,
n represents a second number.
Preferably, the position estimation value of the object to be measured is determined according to a second function and a third function, wherein the third function is calculated in a manner that:
using a weighted least squares method:
Figure BDA0002179113560000042
preferably, the position estimation value of the object to be measured is determined according to the second function and the third function, where the position estimation value of the object to be measured is:
the invention relates to a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm, which comprises the steps of receiving UWB positioning signals sent by a to-be-detected label carried by a to-be-detected object, and acquiring the arrival time parameters and the received signal strength parameters of UWB positioning signals received by each positioning base station; comparing the received signal strength parameters of each positioning base station, and arranging the received signal strength parameters in a descending order to obtain a second number of positioning base stations with the received signal strength parameters arranged in the front; respectively acquiring the arrival time parameters of a second number of positioning base stations, and determining the distance from each second number of positioning base stations to the label to be detected; calculating the distance difference r between the tag to be detected and each of the second number of positioning base stations and the reference base stationif(ii) a And obtaining the distance difference, and obtaining the estimated position of the object to be measured based on a CHAN algorithm. Effectively reduces the influence of non-line-of-sight errors, improves the positioning precision and the positioning resultTo the accuracy of (2).
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of the three-dimensional UWB indoor positioning method based on the improved CHAN algorithm.
FIG. 2 is a schematic structural diagram of an example of three-dimensional UWB indoor positioning based on the improved CHAN algorithm;
fig. 3 is a graph of the error accumulation probability distribution of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
Referring to fig. 1, the present invention provides a flow chart of a three-dimensional UWB indoor positioning method based on an improved CHAN algorithm. Specifically, as shown in fig. 1, the three-dimensional UWB indoor positioning method based on the improved CHAN algorithm may include the following steps:
s101, receiving a UWB positioning signal sent by a to-be-detected label carried by a to-be-detected object, and simultaneously acquiring an arrival time parameter and a received signal strength parameter of each positioning base station for receiving the UWB positioning signal.
In the embodiment of the invention, UWB is a carrier-free communication technology, and data is transmitted by using nanosecond-microsecond-level non-sine wave narrow pulses. By transmitting very low power signals over a wide frequency spectrum, UWB can achieve data transmission rates of hundreds of Mbit/s to Gbit/s over a range of about 10 meters. The anti-interference performance is strong, the transmission rate is high, the system capacity is large, the transmission power is very small, and the communication equipment can realize communication by using the transmission power less than 1 mW. The low transmitting power greatly prolongs the working time of the system power supply. Moreover, the emission power is low, and the influence of electromagnetic wave radiation on a human body is small. Under the environment of a first number of positioning base stations, the first number of positioning base stations respectively receive UWB positioning signals sent by a to-be-detected tag carried by a to-be-detected object, positioning software acquires each positioning base station receives an arrival time parameter and a received signal strength parameter of the UWB positioning signals, wherein the positioning software is UWB positioning software in the prior art.
S102, comparing the received signal strength parameters of the UWB positioning signals received by each positioning base station, and arranging the received signal strength parameters in a descending order to obtain a second number of positioning base stations with the received signal strength parameters arranged in the front.
In the embodiment of the invention, the received signal strength parameter of each positioning base station for receiving the UWB positioning signal is compared according to the variation function of the received signal strength and the distance of the UWB positioning signal in the transmission process. The calculation mode of the change function is as follows:
Figure BDA0002179113560000061
wherein d is the distance between the positioning base station and the label to be detected, d0N is a path loss coefficient for the reference distance; chi shapeθIs a Gaussian random noise variable with mean 0 and variance δ, PL (d)0) For a distance of a label d to be measured0The reference strength of the signal.
According to the calculation mode of the change function, when the noise error in the environment is small and the distance between the noise error and the tag to be detected is short, the received signal strength is high. Therefore, a positioning base station with a large received signal strength parameter for receiving the UWB positioning signal needs to be selected to determine the corresponding positioning base station closest to the object to be measured or with a small noise error. And arranging the received signal strength parameters of the UWB positioning signals received by each positioning base station in a descending order, and acquiring a second number of positioning base stations with the received signal strength parameters arranged in front.
S103, respectively obtaining the time of arrival parameters of the UWB positioning signals received by the second number of positioning base stations, and determining the distance from each second number of positioning base stations to the label to be detected according to the first function
In the embodiment of the present invention, the calculation method of the first function is as follows:
di＝c*ti；
wherein d isiThe distances from the second number of positioning base stations to the labels to be detected; t is tiTime of arrival at which said UWB location signals are received for a second number of location base stations; c is a constant.
And acquiring the time of arrival parameters of the UWB positioning signals received by the second number of positioning base stations respectively, and calculating the distance from each second number of positioning base stations to the tag to be detected respectively by the formula.
S104, calculating the distance difference r between the tag to be detected and each second number of positioning base stations and the reference base stationifObtaining the distance difference rifAnd obtaining the estimated position of the object to be detected based on the CHAN algorithm.
In the embodiment of the invention, the position estimation value of the object to be measured is determined according to the second function and the third function. Wherein the second function is calculated in a manner that:
Figure BDA0002179113560000071
rif＝ri-rf；
ri 2＝(rif+rf)2；
will r isi 2＝(rif+rf)2Unfolding:
2rifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz；
wherein the content of the first and second substances,
ki＝χi 2+yi 2+zi 2，kf＝χf 2+yf 2+zf 2，χif＝χi-χf，yif＝yi-yf，zif＝zi-zf；
the coordinates of the second positioning base stations are BSi (x)i，yi，zi)；riPositioning distances between the base stations and the labels to be detected for the second quantity; r isfIs the distance between the reference base station and the label to be measured;
introducing a measurement error:
rif＝rif 0+c(ti-tf)＝rif 0Δtif；
2r isifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz is written in matrix form:
θ＝h-GaZa；
wherein the content of the first and second substances,
Figure BDA0002179113560000081
Figure BDA0002179113560000082
n represents a second number.
Wherein the third function is calculated in a manner that:
using a weighted least squares method:
Figure BDA0002179113560000083
obtaining a position estimation value of the object to be detected:
Figure BDA0002179113560000084
for example, as shown in fig. 2, the present embodiment simulates a three-dimensional positioning system formed by a UWB wireless sensor network, where the positioning system is formed by seven positioning base stations (UWB base station 1, UWB base station 2, UWB base station 3, UWB base station 4, UWB base station 5, UWB base station 6, and UWB base station 7) deployed indoors and an object to be measured carrying a tag, where an obstruction 1 is located between the UWB base station 3 and the object to be measured carrying the tag, and an obstruction 2 is located between the UWB base station 4 and the object to be measured carrying the tag, so that non-line-of-sight interference exists.
The method comprises the following steps that an object to be detected carries a tag to be detected, the tag to be detected is placed in an environment with seven positioning base stations, the tag to be detected sends UWB signals, the seven positioning base stations receive the UWB positioning signals, and the arrival time parameters and the received signal strength parameters of the UWB positioning signals received by the seven positioning base stations are obtained at the same time; arranging seven received signal strength parameters in a descending order, and taking out five positioning base stations (a UWB base station 1, a UWB base station 2, a UWB base station 5, a UWB base station 6 and a UWB base station 7) with the largest parameters; five positioning base stations are defined by a first function d according to the time of arrival parameter of the received UWB positioning signali＝c*ti(ii) a Respectively calculating the distances between the tag to be detected and the five base stations; selecting the UWB base station 1 of the five positioning reference base stations as the reference base station, and calculating the distance difference r between the tag to be detected and each of the second number of positioning base stations and the reference base station21、r51、r61、r71(ii) a The coordinate values of the five positioning base stations (UWB base station 1, UWB base station 2, UWB base station 5, UWB base station 6, UWB base station 7) are BS1(χ)1，y1，z1)、BS2(χ2，y2，z2)、BS5(χ5，y5，z5)、BS6(χ6，y6，z6)、BS7(χ7，y7，z7) (ii) a The distances from the five positioning base stations to the label to be detected are as follows:
Figure BDA0002179113560000091
Figure BDA0002179113560000092
Figure BDA0002179113560000093
the distance difference is: r is21＝r2-r1；r51＝r5-r1；r61＝r6-r1；r71＝r7-r1；
r21＝r2-r1After the expansion, the following steps are carried out: 2r21r1＝k2-k1-r21 2-2χ21χ-2y21y-2z21z；
Wherein the content of the first and second substances,
k2＝χ2 2+y2 2+z2 2，k1＝χ1 2+y1 2+z1 2，χ21＝χ2-χ1，y21＝y2-y1，z21＝z2-z1；
introducing a measurement error:
r21＝r21 0+c(t2-t1)＝r21 0Δt21；
r51＝r5-r1after the expansion, the following steps are carried out: 2r51r1＝k5-k1-r51 2-2χ51χ-2y51y-2z51z；
Wherein the content of the first and second substances,
k5＝χ5 2+y5 2+z5 2，k1＝χ1 2+y1 2+z1 2，χ51＝χ5-χ1，y51＝y5-y1，z51＝z5-z1；
introducing a measurement error:
r51＝r51 0+c(t5-t1)＝r51 0Δt51；
r61＝r6-r1after the expansion, the following steps are carried out: 2r61r1＝k6-k1-r61 2-2χ61χ-2y61y-2z61z；
Wherein the content of the first and second substances,
k6＝χ6 2+y6 2+z6 2，k1＝χ1 2+y1 2+z1 2，χ61＝χ6-χ1，y61＝y6-y1，z61＝z6-z1；
introducing a measurement error:
r61＝r61 0+c(t6-t1)＝r61 0Δt61；
r71＝r7-r1after the expansion, the following steps are carried out: 2r71r1＝k7-k1-r71 2-2χ71χ-2y71y-2z71z；
Wherein the content of the first and second substances,
k7＝χ7 2+y7 2+z7 2，k1＝χ1 2+y1 2+z1 2，χ71＝χ7-χ1，y71＝y7-y1，z71＝z7-z1；
introducing a measurement error:
r71＝r71 0+c(t7-t1)＝r71 0Δt71；
writing the above equation in matrix form:
θ＝h-GaZa；
wherein the content of the first and second substances,
Figure BDA0002179113560000112
using a weighted least squares method:
the position estimation value of the object to be measured is obtained as follows:
Figure BDA0002179113560000114
as shown in fig. 3, comparing the error accumulation probability distribution curve obtained by the positioning method of the present invention with the positioning method using the conventional CHAN algorithm, the method of the present invention effectively reduces the influence of non-line-of-sight errors, improves the positioning accuracy, and improves the accuracy of the positioning result.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the above embodiments, and various modifications or alterations can be made by those skilled in the art without departing from the spirit and scope of the claims of the present application.

Claims (7)

1. A three-dimensional UWB indoor positioning method based on an improved CHAN algorithm is characterized by comprising the following steps:
under the environment of a first number of positioning base stations, receiving UWB positioning signals sent by a to-be-detected label carried by a to-be-detected object, and simultaneously acquiring the arrival time parameters and the received signal strength parameters of each positioning base station for receiving the UWB positioning signals;
according to the variation function of the received signal strength and the distance of the UWB positioning signals in the transmission process, comparing the received signal strength parameters of the UWB positioning signals received by each positioning base station, and arranging the received signal strength parameters in a descending order to obtain a second number of positioning base stations with the received signal strength parameters arranged in front;
respectively acquiring the arrival time parameters of the second number of positioning base stations for receiving the UWB positioning signals, and determining the distance from each second number of positioning base stations to the tag to be detected according to a first function;
calculating the distance difference between the tag to be detected and each of the second number of positioning base stations and the reference base station, wherein the reference base station f is one of the second number of positioning base stations;
and obtaining the distance difference, and obtaining the estimated position of the object to be measured based on a CHAN algorithm.
2. The three-dimensional UWB indoor location method based on the modified CHAN algorithm of claim 1 wherein the variation function is calculated by:
Figure FDA0002179113550000011
wherein d is the distance between the positioning base station and the label to be detected, d0N is a path loss coefficient for the reference distance; chi shapeθIs a Gaussian random noise variable with mean 0 and variance δ, PL (d)0) For a distance of a label d to be measured0The reference strength of the signal.
3. The three-dimensional UWB indoor location method based on the modified CHAN algorithm of claim 1 wherein the first function is calculated by:
di＝c*ti；
wherein d isiThe distances from the second number of positioning base stations to the labels to be detected; t is tiTime of arrival at which said UWB location signals are received for a second number of location base stations; c is a constant.
4. The improved CHAN algorithm based three-dimensional UWB indoor positioning method of claim 1, wherein said obtaining distance differences and obtaining estimated position of the object to be measured based on the CHAN algorithm comprises:
and determining the position estimation value of the object to be measured according to the second function and the third function.
5. The improved CHAN algorithm based three-dimensional UWB indoor positioning method of claim 4, wherein said determining the position estimate of the object to be measured is based on a second function and a third function, wherein said second function is calculated by:
Figure FDA0002179113550000021
rif＝ri-rf；
ri 2＝(rif+rf)2；
will r isi 2＝(rif+rf)2Unfolding:
2rifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz；
wherein the content of the first and second substances,
ki＝χi 2+yi 2+zi 2，kf＝χf 2+yf 2+zf 2，χif＝χi-χf，yif＝yi-yf，zif＝zi-zf；
the coordinates of the second positioning base stations are BSi (x)i，yi，zi)；riPositioning distances between the base stations and the labels to be detected for the second quantity; r isfIs the distance between the reference base station and the label to be measured;
introducing a measurement error:
rif＝rif 0+c(ti-tf)＝rif 0Δtif；
2r isifrf＝ki-kf-rif 2-2χifχ-2yify-2zifz is written in matrix form:
θ＝h-GaZa；
wherein the content of the first and second substances,
Figure FDA0002179113550000031
Figure FDA0002179113550000032
n represents a second number.
6. The improved CHAN algorithm based three-dimensional UWB indoor positioning method of claim 5 wherein said determining a position estimate of the object is based on a second function and a third function, wherein said third function is calculated by:
using a weighted least squares method:
Figure FDA0002179113550000033
7. the improved CHAN algorithm based three-dimensional UWB indoor positioning method of claim 6, wherein the position estimate of the object is determined according to the second function and the third function, wherein the position estimate of the object is:
Figure FDA0002179113550000034
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CN111766561A (en) * 2020-04-24 2020-10-13 天津大学 Unmanned aerial vehicle positioning method based on UWB technology
CN112637767A (en) * 2020-07-24 2021-04-09 成都精位科技有限公司 Positioning method, positioning device, electronic equipment and readable storage medium
CN113514794A (en) * 2021-04-21 2021-10-19 北京交通大学 Indoor three-dimensional positioning method based on AOA and TDOA
CN115022960A (en) * 2021-02-19 2022-09-06 大唐移动通信设备有限公司 Position identification method and device and processor readable storage medium
CN116437288A (en) * 2023-05-04 2023-07-14 青岛柯锐思德电子科技有限公司 Method for selecting LOS base station algorithm design based on signal strength

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Application publication date: 20191231