CN112066996A - Virtual interpolation positioning method based on disturbance channel model - Google Patents

Virtual interpolation positioning method based on disturbance channel model Download PDF

Info

Publication number
CN112066996A
CN112066996A CN202011160870.7A CN202011160870A CN112066996A CN 112066996 A CN112066996 A CN 112066996A CN 202011160870 A CN202011160870 A CN 202011160870A CN 112066996 A CN112066996 A CN 112066996A
Authority
CN
China
Prior art keywords
signal
virtual
fixed nodes
nodes
fixed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202011160870.7A
Other languages
Chinese (zh)
Other versions
CN112066996B (en
Inventor
赵阳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Civil Aviation University of China
Original Assignee
Civil Aviation University of China
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Civil Aviation University of China filed Critical Civil Aviation University of China
Priority to CN202011160870.7A priority Critical patent/CN112066996B/en
Publication of CN112066996A publication Critical patent/CN112066996A/en
Application granted granted Critical
Publication of CN112066996B publication Critical patent/CN112066996B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

A virtual interpolation positioning method based on a disturbance channel model is provided. The method comprises the steps that signal receivers are uniformly arranged in a grid shape in a space to be detected, and signal transmitters are dispersedly arranged in the space to be detected; obtaining actual signal values at each fixed node; when the signal receiver to be positioned enters a space to be detected, signal values reflected by the signal receivers at all fixed nodes under the condition are obtained; selecting four nodes with the maximum similarity to a signal value reflected by a signal receiver to be positioned, and taking a grid where the four nodes are located as a rough position of the signal receiver to be positioned; and estimating a signal value reflected by a virtual signal receiver at each node uniformly divided in the grid space based on the disturbance channel model, and estimating the position of the signal receiver to be positioned by comparing the similarity of the virtual signal value and the signal value to be positioned. The virtual interpolation of the method is closer to the actually measured data, and the method meets the application requirements of low cost and high precision.

Description

Virtual interpolation positioning method based on disturbance channel model
Technical Field
The invention belongs to the technical field of indoor wireless positioning, and particularly relates to a virtual interpolation positioning method based on a disturbance channel model.
Background
With the continuous development of the internet of things technology, the location-based service is more and more interesting, but the real-time and rapid high-precision positioning technology is still the key and difficult problem of the current research. Traditional wireless location technologies include GPS, bluetooth, ultrasound, ultra-wideband, Wi-Fi, computer vision, ultra-high frequency radio frequency identification (UHF RFID), and the like. For the positioning technology in the indoor environment, especially for the application environments such as needing to position a large number of articles and personnel, the passive UHF RFID becomes a hotspot of indoor positioning research in recent years by virtue of the advantages of non-contact, low manufacturing cost, easiness in laying, low power consumption and the like.
Because indoor wireless channels are complex and changeable, a positioning method based on scene analysis in a passive UHF RFID positioning technology is one of the key directions of current research, the scene analysis method is to introduce a fixed node, deploy a reference tag with known position information at the fixed node, select an adjacent reference tag by comparing the similarity of wireless signal information between the reference tag and a tag to be positioned, and estimate the position information of the tag to be positioned by using the adjacent reference tag. The fixed nodes are positioned at the intersection points in the uniform grid, and in order to improve the positioning accuracy, the traditional method can increase the deployment density of the fixed nodes as much as possible under the premise of budget conditions. However, since mutual coupling influence is generated between fixed nodes, the accuracy of selecting adjacent reference tags is rather reduced when the density is too high, and the positioning accuracy is further reduced, so that the improvement of the reference matching performance on the premise of not increasing the density of the reference tags becomes a key problem of research. At present, the concept of virtual reference tags has been introduced in research, and the reference matching is increased by estimating the signal value reflected by the signal receiver at the virtual node, so that the laying density of the reference tags is not increased, the coupling risk of tag antennas is reduced, and the accuracy of matching and positioning can be improved.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a virtual interpolation positioning method based on a disturbed channel model.
In order to achieve the above object, the virtual interpolation positioning method based on the disturbance channel model provided by the present invention comprises the following steps performed in sequence:
1) uniformly arranging a plurality of signal receivers serving as fixed nodes in a grid shape at a certain interval in a space to be detected, setting a label for each grid, and dispersedly arranging signal transmitters in the space to be detected;
2) transmitting a signal by using a signal transmitter and receiving a signal reflected by each fixed node to obtain an actual signal value reflected by each fixed node;
3) when a signal receiver t to be positioned is attached to a target to be positioned and enters a space to be detected, signal values reflected by all fixed nodes under the condition are obtained, and the similarity between the signal values reflected by the signal receiver t to be positioned and the signal values reflected by the fixed nodes is compared;
4) sorting all the similarities in a descending order, selecting a fixed node with larger similarity as an adjacent fixed node, and determining a label q of a grid where a signal receiver t to be positioned is located through the adjacent fixed node;
5) performing virtual fixed node interpolation in the grid according to the label q of the grid where the signal receiver t to be positioned is located, taking one fourth of the interval of the fixed nodes as the interval of the virtual fixed nodes, and marking labels of sub-grids divided by the virtual fixed nodes; under the condition that the positions of four fixed nodes, the positions of virtual fixed nodes and the distance between the grid and a signal transmitter, which are contained in the grid with the label q, are known, a signal value reflected by the virtual fixed nodes is estimated by using a disturbance channel model, the similarity between a signal receiver t to be positioned and the signal value reflected by the virtual fixed nodes is compared, the virtual fixed nodes with higher similarity are selected as adjacent virtual fixed nodes, the sub-grid where the signal receiver t to be positioned is located is determined by the adjacent virtual fixed nodes, and the label q is marked as1；
6) Numbering q according to the method of step 5)1And then carrying out virtual fixed node interpolation on the sub-grids to obtain a final adjacent virtual fixed node, and estimating the coordinate of the signal receiver t to be positioned by the final adjacent virtual fixed node.
In step 1), the method of uniformly arranging a plurality of signal receivers as fixed nodes in a grid shape at a certain interval in a space to be detected, setting a label for each grid, and dispersedly arranging signal transmitters in the space to be detected comprises:
after num signal transmitters and n signal receivers which need to be arranged in a space to be detected are determined, the n signal receivers are uniformly arranged in the space to be detected as fixed nodes according to the g-meter interval, so that the space to be detected is uniformly divided into a plurality of grids, the fixed nodes are positioned at the intersection points of the grids, a label is set for each grid, and the num signal transmitters are dispersedly arranged in the space to be detected.
In step 2), the method for obtaining the actual signal value reflected by each fixed node by using the signal transmitter to transmit the signal and receiving the signal reflected by each fixed node is as follows:
and (3) transmitting a signal by using a signal transmitter and receiving the signal reflected by each fixed node, repeating the experiment for a plurality of times, then taking an average value, and recording the average value as an actual signal value:
Figure BDA0002744190100000031
in step 3), the method for obtaining the signal values reflected by all the fixed nodes under the condition after the signal receiver t to be positioned is attached to the target to be positioned and enters the space to be detected, and comparing the similarity between the signal values reflected by the signal receiver t to be positioned and the signal values reflected by the fixed nodes is as follows:
the signal emitter is used for emitting signals and receiving signals reflected by all the fixed nodes, the mean value of the signal values reflected by all the fixed nodes under m times of experiments is counted and recorded as:
Figure BDA0002744190100000032
then, the signal mean values under m experiments reflected by the signal receiver t to be positioned are respectively compared
Figure BDA0002744190100000033
Similarity to the mean of the signals reflected by each fixed node r 1:
Figure BDA0002744190100000041
in step 4), the method for sorting all the similarities in a descending order, selecting a fixed node with a larger similarity as an adjacent fixed node, and determining the label q of the grid where the signal receiver t to be positioned is located by the adjacent fixed node includes:
sorting all the similarities obtained in the step 3) in a descending order to obtain { S1，S2，...，SnAnd selecting the fixed nodes corresponding to the first k similarities as adjacent fixed nodes, and determining the label q of the grid where the signal receiver t to be positioned is located by using the positions of the adjacent fixed nodes.
In step 5), performing virtual fixed node interpolation in the grid according to the label q of the grid where the signal receiver t to be positioned is located, taking one fourth of the distance between the fixed nodes as the distance between the virtual fixed nodes, and marking the labels of the sub-grids divided by the virtual fixed nodes; under the condition that the positions of four fixed nodes, the positions of virtual fixed nodes and the distance between the grid and a signal transmitter, which are contained in the grid with the label q, are known, a signal value reflected by the virtual fixed nodes is estimated by using a disturbance channel model, the similarity between a signal receiver t to be positioned and the signal value reflected by the virtual fixed nodes is compared, the virtual fixed nodes with higher similarity are selected as adjacent virtual fixed nodes, the sub-grid where the signal receiver t to be positioned is located is determined by the adjacent virtual fixed nodes, and the label q is marked as1The method comprises the following steps:
performing virtual fixed node interpolation in a grid of a label q where a signal receiver t to be positioned is located, taking one fourth of the g-meter distance of the fixed nodes determined in the step 1) as the distance of the virtual fixed nodes, obtaining n1 virtual fixed nodes, and marking labels of sub-grids divided by the virtual fixed nodes;
the signal values reflected by the four fixed nodes contained in the grid labeled q are:
Figure BDA0002744190100000042
the distances between the n1 virtual fixed nodes and the four fixed nodes are respectively:
Figure BDA0002744190100000051
the distances between the four fixed nodes and the signal emitter are respectively as follows:
Figure BDA0002744190100000052
the distances between the n1 virtual fixed nodes and the signal emitter are respectively:
Figure BDA0002744190100000053
by using the distance between the virtual fixed node and the virtual fixed node in g/(2)wEstimating a signal value of a virtual fixed node by using fixed nodes within a meter range, wherein w represents the cycle number;
for the ith virtual fixed node, the adjacent fixed node is the jth fixed node, and the signal value thereof
Figure BDA0002744190100000054
Comprises the following steps:
Figure BDA0002744190100000055
wherein, A, a is related to the environment and the type of the signal receiver;
and then comparing the similarity of the signal receiver t to be positioned and the signal value estimated at the virtual fixed node i:
Figure BDA0002744190100000056
sequencing all the similarities in descending order to obtain { S'1,S'2,...,S'n1And selecting the first k virtual fixed nodes corresponding to the similarity as adjacent virtual fixed nodes, and further determining the sub-grid where the signal receiver to be positioned is located by the adjacent virtual fixed nodes, wherein the labels are marked asq1。
In step 6), the method according to step 5) is labeled with the reference number q1The sub-grid carries out virtual fixed node interpolation to obtain a final adjacent virtual fixed node, and the method for estimating the coordinate of the signal receiver t to be positioned by the final adjacent virtual fixed node comprises the following steps:
numbering q according to the method of step 5)1And then, performing virtual fixed node interpolation on the sub-grids to obtain k final adjacent virtual fixed nodes, and determining the weight of each final adjacent virtual fixed node by utilizing the similarity between the signal value corresponding to the k final adjacent virtual fixed nodes and the signal value corresponding to the signal receiver t to be positioned:
the coordinates of the k final neighboring virtual fixed nodes are:
N(x1,y1,z1),N(x2,y2,z2),...,N(xk,yk,zk) (9)
calculating the weight of k final neighboring virtual fixed nodes using the similarity of the signal values obtained by equation (8):
Figure BDA0002744190100000061
and finally, determining the coordinates (x, y, z) of the signal receiver t to be positioned by using the coordinates and weights of the k final adjacent virtual fixed nodes:
Figure BDA0002744190100000062
compared with the prior art, the invention has the beneficial effects that:
firstly, the fixed nodes are arranged at the intersection points of the uniform grids, and the distance between the fixed nodes is set to be larger so as to weaken the negative influence of the mutual coupling of the antennas between the fixed nodes on the positioning precision. Because the fixed node and the signal receiver to be positioned are both positioned in the same propagation environment, the method has good robustness to dynamic environment factors. And finally, a disturbing signal model is provided, the signal values reflected by the virtual fixed nodes are realized based on the model, and the positioning can be completed by utilizing the similarity of the signals reflected by the virtual fixed nodes on the premise of not increasing the density of the fixed nodes. Experimental results show that the method preliminarily judges that the error of the signal receiver to be positioned is less than 10cm, so that the positioning performance is high, hardware equipment is simple and easy to realize, and the method meets the application requirements of low cost and high precision.
Drawings
Fig. 1 is a schematic diagram of a layout of reference tags in an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention are further described in detail with reference to the accompanying drawings and specific embodiments, which are merely illustrative of the present invention and are not intended to limit the present invention.
As shown in fig. 1, in this embodiment, a passive ultrahigh frequency radio frequency identification technology is taken as an example to describe the virtual interpolation positioning method based on the disturbance channel model provided by the present invention, an adopted signal transmitter is represented by a card reader including a transmitting/receiving integrated antenna, a signal receiver to be positioned is represented by a passive radio frequency tag to be positioned (tag to be positioned), a fixed node is represented by a passive radio frequency tag with a known position, which is called a reference tag, and a transmitting signal frequency is 922 MHz.
Step 1, deploying a reference label:
the size of the space to be detected is a two-dimensional space of 4 x 4 meters, the card readers are connected with a computer for uploading data, and four card readers are deployed at four corners of the space to be detected and face the space to be detected, as shown in fig. 1.
Reference tags are deployed at the intersection points of the grids, 16 grids are planned according to the interval distance of 1 meter, and the planned grids are assumed to contain 25 fixed nodes, and each fixed node is called a reference tag.
Step 2, counting the signal value reflected by the reference label:
the card reader is used for transmitting signals and receiving signals reflected from all the reference labels, the average value is obtained after repeated experiments, and the theoretical signal value corresponding to all the reference labels is recorded as:
Figure BDA0002744190100000071
and 3, screening adjacent reference labels:
when a label t to be positioned is attached to a target to be positioned and enters a space to be detected, signal values reflected by all reference labels under the condition are obtained, and the similarity between the signal value reflected by the label t to be positioned and the signal value reflected by the reference labels is compared;
the mean value of the signal values corresponding to the reference labels in the m experiments is counted and recorded as
Figure BDA0002744190100000081
Then, the signal mean values of m times of experiments reflected by the labels t to be positioned are respectively compared
Figure BDA0002744190100000082
Similarity to the mean of the signals reflected by each reference label r 1:
Figure BDA0002744190100000083
step 4, preliminarily determining the label q of the grid where the label to be positioned is located:
sorting all the similarities in descending order to obtain { S1，S2，...，S25And selecting reference labels corresponding to the first 6 similarities as adjacent reference labels, and determining the label q of the grid where the label to be positioned is located by using the positions of the adjacent reference labels. For example, the first grid has a corresponding reference label of {1,2,6,7 }.
Step 5, estimating a signal value corresponding to the virtual reference label:
further dividing the mesh at intervals of 25cm within the mesh of reference sign q to obtain 21 virtual reference labels, and marking the reference signs of the sub-meshes divided by the virtual fixed nodes;
the four reference tags contained in the grid labeled q reflect the following signal values:
Figure BDA0002744190100000084
the distances between the 21 virtual reference tags and the four reference tags are respectively as follows:
Figure BDA0002744190100000085
the distances from the four reference tags to the four readers are respectively as follows:
Figure BDA0002744190100000086
the distances from the 21 virtual reference tags to the four readers are respectively as follows:
Figure BDA0002744190100000087
with a spacing of 1/(2) from the virtual reference labelwEstimating a signal value of the virtual reference tag by the reference tags within the range of meters, wherein w represents the cycle number; taking the 1 st virtual reference tag as an example, assume that its neighboring reference tag is the first reference tag, and its signal value
Figure BDA0002744190100000088
Comprises the following steps:
Figure BDA0002744190100000091
where a, a is related to the environment and the type of signal receiver.
And then comparing the similarity of the signal values of the tag t to be positioned and the virtual reference tag i:
Figure BDA0002744190100000092
sorting the similarity in descending order to obtain { S'1,S'2,...,S'21}. Selecting the virtual reference labels corresponding to the first 6 similarities as adjacent virtual reference labels, determining the submesh of the label t to be positioned by the adjacent virtual reference labels, and marking as q1。
Step 6, estimating the position of the label to be positioned:
numbering q according to the method of step 5)1And then, performing virtual reference label interpolation on the sub-grids to obtain k final adjacent virtual reference labels, and determining the weight of each final adjacent virtual reference label by utilizing the similarity between the signal value corresponding to the k final adjacent virtual reference labels and the signal value corresponding to the label t to be positioned:
the coordinates of the 6 final adjacent virtual reference tags are:
N(x1,y1,z1),N(x2,y2,z2),...,N(x6,y6,z6) (20)
using the similarity of the signal values obtained by equation (19), the weights of the 6 final neighboring virtual reference tags are calculated:
Figure BDA0002744190100000093
and finally, determining the coordinates (x, y, z) of the tag t to be positioned by utilizing the coordinates and the weights of the 6 final adjacent virtual reference tags:
Figure BDA0002744190100000101
assuming that the tag to be located enters the first grid, the actual location is (25,35) (cm), the location of the tag to be located is estimated by equation (22) in step 4 (which can be determined to be within the first grid.) to be about: (21,40) (cm), the position estimation error is about: 6.40 cm. The label used in this test is about 5cm x 5cm, and the size of the article to which the label is attached is generally larger than the size of the label, and it can be seen that this error is in the order of magnitude of the article's own size, so this error can be considered to be within an acceptable range.
While the present invention has been described with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments, which are illustrative only and not restrictive, and various modifications which do not depart from the spirit of the present invention and which are intended to be covered by the claims of the present invention may be made by those skilled in the art.

Claims (7)

1. A virtual interpolation positioning method based on a disturbance channel model is characterized in that: the virtual interpolation positioning method based on the disturbance channel model comprises the following steps in sequence:
1) uniformly arranging a plurality of signal receivers serving as fixed nodes in a grid shape at a certain interval in a space to be detected, setting a label for each grid, and dispersedly arranging signal transmitters in the space to be detected;
2) transmitting a signal by using a signal transmitter and receiving a signal reflected by each fixed node to obtain an actual signal value reflected by each fixed node;
3) when a signal receiver t to be positioned is attached to a target to be positioned and enters a space to be detected, signal values reflected by all fixed nodes under the condition are obtained, and the similarity between the signal values reflected by the signal receiver t to be positioned and the signal values reflected by the fixed nodes is compared;
4) sorting all the similarities in a descending order, selecting a fixed node with larger similarity as an adjacent fixed node, and determining a label q of a grid where a signal receiver t to be positioned is located through the adjacent fixed node;
5) according to the mark q of the grid where the signal receiver t to be positioned is located, the mark q is positionedCarrying out virtual fixed node interpolation in the grids, taking one fourth of the distance between the fixed nodes as the distance between the virtual fixed nodes, and marking the labels of the sub-grids divided by the virtual fixed nodes; under the condition that the positions of four fixed nodes, the positions of virtual fixed nodes and the distance between the grid and a signal transmitter, which are contained in the grid with the label q, are known, a signal value reflected by the virtual fixed nodes is estimated by using a disturbance channel model, the similarity between a signal receiver t to be positioned and the signal value reflected by the virtual fixed nodes is compared, the virtual fixed nodes with higher similarity are selected as adjacent virtual fixed nodes, the sub-grid where the signal receiver t to be positioned is located is determined by the adjacent virtual fixed nodes, and the label q is marked as1；
6) Numbering q according to the method of step 5)1And then carrying out virtual fixed node interpolation on the sub-grids to obtain a final adjacent virtual fixed node, and estimating the coordinate of the signal receiver t to be positioned by the final adjacent virtual fixed node.
2. The method according to claim 1, wherein the virtual interpolation positioning method based on the perturbation channel model comprises: in step 1), the method of uniformly arranging a plurality of signal receivers as fixed nodes in a grid shape at a certain interval in a space to be detected, setting a label for each grid, and dispersedly arranging signal transmitters in the space to be detected comprises:
after num signal transmitters and n signal receivers which need to be arranged in a space to be detected are determined, the n signal receivers are uniformly arranged in the space to be detected as fixed nodes according to the g-meter interval, so that the space to be detected is uniformly divided into a plurality of grids, the fixed nodes are positioned at the intersection points of the grids, a label is set for each grid, and the num signal transmitters are dispersedly arranged in the space to be detected.
3. The method according to claim 1, wherein the virtual interpolation positioning method based on the perturbation channel model comprises: in step 2), the method for obtaining the actual signal value reflected by each fixed node by using the signal transmitter to transmit the signal and receiving the signal reflected by each fixed node is as follows:
and (3) transmitting a signal by using a signal transmitter and receiving the signal reflected by each fixed node, repeating the experiment for a plurality of times, then taking an average value, and recording the average value as an actual signal value:
Figure FDA0002744190090000021
4. the method according to claim 1, wherein the virtual interpolation positioning method based on the perturbation channel model comprises: in step 3), the method for obtaining the signal values reflected by all the fixed nodes under the condition after the signal receiver t to be positioned is attached to the target to be positioned and enters the space to be detected, and comparing the similarity between the signal values reflected by the signal receiver t to be positioned and the signal values reflected by the fixed nodes is as follows:
the signal emitter is used for emitting signals and receiving signals reflected by all the fixed nodes, the mean value of the signal values reflected by all the fixed nodes under m times of experiments is counted and recorded as:
Figure FDA0002744190090000022
then, the signal mean values under m experiments reflected by the signal receiver t to be positioned are respectively compared
Figure FDA0002744190090000031
Similarity to the mean of the signals reflected by each fixed node r 1:
Figure FDA0002744190090000032
5. the method according to claim 1, wherein the virtual interpolation positioning method based on the perturbation channel model comprises: in step 4), the method for sorting all the similarities in a descending order, selecting a fixed node with a larger similarity as an adjacent fixed node, and determining the label q of the grid where the signal receiver t to be positioned is located by the adjacent fixed node includes:
sorting all the similarities obtained in the step 3) in a descending order to obtain { S1，S2，...，SnAnd selecting the fixed nodes corresponding to the first k similarities as adjacent fixed nodes, and determining the label q of the grid where the signal receiver t to be positioned is located by using the positions of the adjacent fixed nodes.
6. The method according to claim 1, wherein the virtual interpolation positioning method based on the perturbation channel model comprises: in step 5), performing virtual fixed node interpolation in the grid according to the label q of the grid where the signal receiver t to be positioned is located, taking one fourth of the distance between the fixed nodes as the distance between the virtual fixed nodes, and marking the labels of the sub-grids divided by the virtual fixed nodes; under the condition that the positions of four fixed nodes, the positions of virtual fixed nodes and the distance between the grid and a signal transmitter, which are contained in the grid with the label q, are known, a signal value reflected by the virtual fixed nodes is estimated by using a disturbance channel model, the similarity between a signal receiver t to be positioned and the signal value reflected by the virtual fixed nodes is compared, the virtual fixed nodes with higher similarity are selected as adjacent virtual fixed nodes, the sub-grid where the signal receiver t to be positioned is located is determined by the adjacent virtual fixed nodes, and the label q is marked as1The method comprises the following steps:
performing virtual fixed node interpolation in a grid of a label q where a signal receiver t to be positioned is located, taking one fourth of the g-meter distance of the fixed nodes determined in the step 1) as the distance of the virtual fixed nodes, obtaining n1 virtual fixed nodes, and marking labels of sub-grids divided by the virtual fixed nodes;
the signal values reflected by the four fixed nodes contained in the grid labeled q are:
Figure FDA0002744190090000041
the distances between the n1 virtual fixed nodes and the four fixed nodes are respectively:
Figure FDA0002744190090000042
the distances between the four fixed nodes and the signal emitter are respectively as follows:
Figure FDA0002744190090000043
the distances between the n1 virtual fixed nodes and the signal emitter are respectively:
Figure FDA0002744190090000044
by using the distance between the virtual fixed node and the virtual fixed node in g/(2)wEstimating a signal value of a virtual fixed node by using fixed nodes within a meter range, wherein w represents the cycle number;
for the ith virtual fixed node, the adjacent fixed node is the jth fixed node, and the signal value thereof
Figure FDA0002744190090000045
Comprises the following steps:
Figure FDA0002744190090000046
wherein, A, a is related to the environment and the type of the signal receiver;
and then comparing the similarity of the signal receiver t to be positioned and the signal value estimated at the virtual fixed node i:
Figure FDA0002744190090000047
sorting all the similarities in descending order to obtain { S1',S2',...,Sn1' }, selecting the virtual fixed nodes corresponding to the former k similarities as adjacent virtual fixed nodes, and further determining the sub-grid where the signal receiver to be positioned is located by the adjacent virtual fixed nodes, wherein the label is marked as q1。
7. The method according to claim 1 or 8, wherein: in step 6), the method according to step 5) is labeled with the reference number q1The sub-grid carries out virtual fixed node interpolation to obtain a final adjacent virtual fixed node, and the method for estimating the coordinate of the signal receiver t to be positioned by the final adjacent virtual fixed node comprises the following steps:
numbering q according to the method of step 5)1And then, performing virtual fixed node interpolation on the sub-grids to obtain k final adjacent virtual fixed nodes, and determining the weight of each final adjacent virtual fixed node by utilizing the similarity between the signal value corresponding to the k final adjacent virtual fixed nodes and the signal value corresponding to the signal receiver t to be positioned:
the coordinates of the k final neighboring virtual fixed nodes are:
N(x1,y1,z1),N(x2,y2,z2),...,N(xk,yk,zk) (9)
calculating the weight of k final neighboring virtual fixed nodes using the similarity of the signal values obtained by equation (8):
Figure FDA0002744190090000051
and finally, determining the coordinates (x, y, z) of the signal receiver t to be positioned by using the coordinates and weights of the k final adjacent virtual fixed nodes:
Figure FDA0002744190090000052
CN202011160870.7A 2020-10-27 2020-10-27 Virtual interpolation positioning method based on disturbance channel model Active CN112066996B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011160870.7A CN112066996B (en) 2020-10-27 2020-10-27 Virtual interpolation positioning method based on disturbance channel model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011160870.7A CN112066996B (en) 2020-10-27 2020-10-27 Virtual interpolation positioning method based on disturbance channel model

Publications (2)

Publication Number Publication Date
CN112066996A true CN112066996A (en) 2020-12-11
CN112066996B CN112066996B (en) 2023-09-12

Family

ID=73655978

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011160870.7A Active CN112066996B (en) 2020-10-27 2020-10-27 Virtual interpolation positioning method based on disturbance channel model

Country Status (1)

Country Link
CN (1) CN112066996B (en)

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101349746A (en) * 2008-09-06 2009-01-21 黄以华 Wireless radio frequency positioning method based on virtual reference label algorithm
CN101587182A (en) * 2009-06-25 2009-11-25 华南理工大学 Locating method for RFID indoor locating system
CN102338866A (en) * 2011-06-02 2012-02-01 西安理工大学 Radio frequency indoor positioning method based on virtual tag algorithm
CN102736061A (en) * 2012-05-31 2012-10-17 四川研成通信科技有限公司 RFID (Radio Frequency Identification )-based grid positioning system and method
US20130273938A1 (en) * 2011-01-13 2013-10-17 Panasonic Corporation Method for determination of wireless terminals positions and associated system and apparatus thereof
CN104535960A (en) * 2014-12-29 2015-04-22 华南理工大学 Indoor rapid positioning method based on RFID
CN104977561A (en) * 2014-04-04 2015-10-14 江苏中科泛联物联网科技股份有限公司 Positioning algorithm based on virtual tags and cyclic check
US20160187460A1 (en) * 2014-05-14 2016-06-30 Shenyang Institute Of Automation Of The Chinese Academy Of Sciences Rssi positioning method based on frequency-hopping spread spectrum technology
CN107907856A (en) * 2017-10-24 2018-04-13 东南大学 A kind of RFID localization methods and system based on virtual reference label
CN109444812A (en) * 2018-09-28 2019-03-08 西北工业大学 A kind of RSSI indoor orientation method introducing dynamic threshold
CN110888107A (en) * 2020-01-15 2020-03-17 南宁职业技术学院 Novel RFID (radio frequency identification) positioning system based on cubic spline interpolation and using method

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101349746A (en) * 2008-09-06 2009-01-21 黄以华 Wireless radio frequency positioning method based on virtual reference label algorithm
CN101587182A (en) * 2009-06-25 2009-11-25 华南理工大学 Locating method for RFID indoor locating system
US20130273938A1 (en) * 2011-01-13 2013-10-17 Panasonic Corporation Method for determination of wireless terminals positions and associated system and apparatus thereof
CN102338866A (en) * 2011-06-02 2012-02-01 西安理工大学 Radio frequency indoor positioning method based on virtual tag algorithm
CN102736061A (en) * 2012-05-31 2012-10-17 四川研成通信科技有限公司 RFID (Radio Frequency Identification )-based grid positioning system and method
CN104977561A (en) * 2014-04-04 2015-10-14 江苏中科泛联物联网科技股份有限公司 Positioning algorithm based on virtual tags and cyclic check
US20160187460A1 (en) * 2014-05-14 2016-06-30 Shenyang Institute Of Automation Of The Chinese Academy Of Sciences Rssi positioning method based on frequency-hopping spread spectrum technology
CN104535960A (en) * 2014-12-29 2015-04-22 华南理工大学 Indoor rapid positioning method based on RFID
CN107907856A (en) * 2017-10-24 2018-04-13 东南大学 A kind of RFID localization methods and system based on virtual reference label
CN109444812A (en) * 2018-09-28 2019-03-08 西北工业大学 A kind of RSSI indoor orientation method introducing dynamic threshold
CN110888107A (en) * 2020-01-15 2020-03-17 南宁职业技术学院 Novel RFID (radio frequency identification) positioning system based on cubic spline interpolation and using method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
严大虎;徐杨杰;: "融合ZigBee的改进射频识别室内定位算法研究", 系统仿真学报, no. 11 *
李军怀;孙转宜;王一乐;王锋;: "基于虚拟参考标签的RFID定位系统构建方法", 计算机科学, no. 04 *
邓遂;邓瀚林;潘强;刘海涛;: "引入RSSI指纹抖动量的室内定位改进算法", 计算机工程, no. 02 *

Also Published As

Publication number Publication date
CN112066996B (en) 2023-09-12

Similar Documents

Publication Publication Date Title
CN101639527B (en) K nearest fuzzy clustering WLAN indoor locating method based on REE-P
CN109444813B (en) RFID indoor positioning method based on BP and DNN double neural networks
Ma et al. The optimization for hyperbolic positioning of UHF passive RFID tags
CN105101408A (en) Indoor positioning method based on distributed AP selection strategy
CN108696932A (en) It is a kind of using CSI multipaths and the outdoor fingerprint positioning method of machine learning
CN104038901B (en) Indoor positioning method for reducing fingerprint data acquisition workload
CN101131432A (en) Positioning method for wireless radio frequency recognition system and device thereof
Peng et al. Deep convolutional neural network for passive RFID tag localization via joint RSSI and PDOA fingerprint features
CN104507163B (en) A kind of RFID indoor locating systems and method using class honeycomb arrangement
CN104330771A (en) Indoor RFID precise positioning method and device
CN106772218B (en) Localization method is classified based on mobile RFID reader warehouse package plan-position
CN105093175B (en) A kind of three dimension location implementation method based on RFID middleware
CN110187333B (en) RFID label positioning method based on synthetic aperture radar technology
CN109640390A (en) It is a kind of based on refer to RSSI profile UHF RFID relative positioning method
CN106932752A (en) A kind of real-time indoor orientation method based on RF phse monitoring
CN104376349B (en) RFID (radio frequency identification) reader-writer positioning method based on boundary labels
CN104459621A (en) RFID reader antenna positioning method and system
CN109034293A (en) RFID intelligent supervision commodity shelf system framework and method
El Abkari et al. Real time positioning over WSN and RFID network integration
CN112415470B (en) Target positioning method based on signal fluctuation condition
CN112066996B (en) Virtual interpolation positioning method based on disturbance channel model
CN109640253B (en) Mobile robot positioning method
CN109362036A (en) A kind of multi-modal indoor orientation method combined based on image with WIFI
CN108306944A (en) A kind of laboratory's sample distribution formula positioning system based on RFID
CN105404908B (en) High-precision RFID path tracings sorting equipment based on line element geometry and its algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
EE01 Entry into force of recordation of patent licensing contract
EE01 Entry into force of recordation of patent licensing contract

Application publication date: 20201211

Assignee: Inner Mongolia Qidi Clean Energy Technology Research Co.,Ltd.

Assignor: CIVIL AVIATION University OF CHINA

Contract record no.: X2024980002337

Denomination of invention: Virtual interpolation positioning method based on disturbance channel model

Granted publication date: 20230912

License type: Common License

Record date: 20240228