阅读说明：本技术 一种室内定位方法 (Indoor positioning method ) 是由 林凡 刘晨阳 张秋镇 于 2021-06-11 设计创作，主要内容包括：本发明提供的一种室内定位方法,通过多个读写器分别采集待定位的电子标签的信号强度数据；根据对数距离路径损耗模型和所述信号强度数据,得到所述电子标签分别与多个所述读写器的距离；根据所述电子标签分别与多个所述读写器的距离,通过似然函数和最大似然估计原理,得到所述电子标签的粗定位位置；通过环境影响因子调整模型修正所述似然函数中的环境影响因子；计算修正后的环境影响因子的方差；当所述方差满足预设条件时,根据所述方差和所述粗定位位置,得到所述电子标签的精确位置,本发明采用中值滤波技术,以及粗定位、修正环境影响因子、调整方差、判定循环程序,具有易实施、精度高的优点,并能实现连续实时定位。(The invention provides an indoor positioning method, which comprises the steps of respectively collecting signal intensity data of an electronic tag to be positioned through a plurality of readers; obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data; obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors; when the variance meets the preset condition, the accurate position of the electronic tag is obtained according to the variance and the coarse positioning position.)

1. An indoor positioning method, characterized in that the method comprises:

respectively acquiring signal intensity data of the electronic tag to be positioned by a plurality of readers;

obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data;

obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle;

correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model;

calculating the variance of the corrected environmental impact factors;

and when the variance meets a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position.

2. The indoor positioning method of claim 1, wherein the acquiring, by the plurality of readers/writers, the signal intensity data of the electronic tag to be positioned, respectively, specifically comprises:

identifying a plurality of readers-writers meeting a preset threshold condition of a wireless sensing network;

the multiple readers continuously acquire the signal intensity of the electronic tag to be positioned for preset times respectively;

selecting a median value of signal intensity data of each reader-writer continuously collected for a preset number of times as sampled signal intensity to obtain signal intensity data collected by a plurality of reader-writers, wherein the signal intensity data comprise signal intensities collected by the plurality of reader-writers to obtain the electronic tag.

3. The indoor positioning method according to claim 1, wherein the obtaining distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal strength data specifically includes:

using logarithmic distance path loss modelCalculating the distances between the electronic tags and the plurality of readers-writers respectively, wherein,

p (d) is the signal strength when the distance between the reader and the electronic tag is d, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀The signal intensity of time, eta is an attenuation factor, sigma is an environmental influence factor, and xi is a zero-mean orthogonal distribution random variable with standard deviation of sigma.

4. The indoor positioning method according to claim 1, wherein the obtaining of the coarse positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle specifically includes:

according to N reader-writersTo signal strength data P ═ P₁ P₂ … P_n]And the calculated corresponding distance D ═ D₁d₂ … d_n]；

According to the likelihood function of the obtained signal intensity P of the logarithmic distance path loss model:

when L (P | D) is maximum, the coarse positioning position of the electronic tag is obtained, namely

Wherein the content of the first and second substances,x and y are coordinates of the electronic tag, x_iAnd y_iCoordinates of N readers/writers, respectively, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀Signal strength in time, ξ represents an orthogonally distributed random variable with a standard deviation σ and a mean μ, η is an attenuation factor, l (P | (x, y) represents a function of each measurement point (x, y) with respect to the blind node signal strength P,the average value of the signal strength data received by the N readers.

5. The indoor positioning method according to claim 1, wherein the modifying the environmental impact factor in the likelihood function by the environmental impact factor adjustment model specifically includes:

adjusting the model by the environmental impact factor:correcting an environment factor sigma in the likelihood function; wherein σ_i ⁿIs σ before adjustment_i，σ_i ⁿ⁺¹For corrected sigma_iWherein, in the step (A),d_ifor the mapping distance of the logarithmic distance path loss model,distance is calculated for the estimated coordinates, and η is the attenuation factor.

6. The indoor positioning method of claim 5, wherein the calculating the variance of the corrected environmental impact factor specifically comprises:

by the formulaCalculating to obtain the variance sigma of the corrected environmental influence factor²Wherein σ₀ ²Is the initial environmental impact factor variance.

7. The indoor positioning method according to claim 6, wherein when the variance satisfies a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position specifically includes:

when the variance σ is²When the variance sigma is less than a preset environmental impact factor value²Substituting the rough positioning position to obtain the coordinate of the precise positioning position

8. The indoor positioning method of claim 1, further comprising: and when the variance is not less than the preset environmental impact factor value, obtaining the rough positioning position of the electronic tag through the likelihood function and the maximum likelihood estimation principle again, correcting the environmental impact factor and recalculating the variance, judging the magnitude relation between the recalculated variance and the preset environmental impact factor value until the variance is less than the preset environmental impact factor value, and substituting the newly obtained variance into the newly obtained rough positioning position to obtain the accurate coordinate of the electronic tag.

Technical Field

The invention relates to the technical field of wireless positioning, in particular to an indoor positioning method.

Background

With the development of the technology of the internet of things, people put forward higher requirements on the positioning technology in the main aspect of the internet of things. Because the indoor environment is complex, the space is small, and various interferences exist, the indoor positioning technology is a certain hotspot and difficulty in positioning research.

The indoor positioning technology needs to accurately provide position information of personnel/equipment in real time, and currently, the mainly adopted indoor positioning technology is an RFID technology (Radio Frequency Identification ) or a ZigBee technology.

The RFID basic principle is that the space coupling (inductive or electromagnetic coupling) or the reflection transmission characteristic of a radio frequency signal is utilized to realize the automatic identification of an identified object, and the received signal strength RSSI or time difference is used to determine the space position of the object to be detected through a certain positioning algorithm. But this technique requires full networking of the devices and does not support continuous positioning.

The ZigBee technology adopts a ZigBee technology framework as a support, networking is carried out by combining a network to collect data, the data are analyzed and stored through a monitoring host, the analyzed data are projected to a terminal, and real-time positioning of terminal equipment is realized. However, in the scheme, the positioning is calculated by a plurality of devices, so that the networking requirement and the background operation requirement are high, and the positioning precision operation requirement is influenced.

Therefore, the prior art is difficult to realize continuous real-time accurate positioning indoors.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides an indoor positioning method, which can realize indoor continuous positioning and has high positioning precision.

The embodiment of the invention provides an indoor positioning method, which comprises the following steps:

respectively acquiring signal intensity data of the electronic tag to be positioned by a plurality of readers;

obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data;

obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle;

correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model;

calculating the variance of the corrected environmental impact factors;

and when the variance meets a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position.

Preferably, the acquiring, by the plurality of readers, the signal intensity data of the electronic tag to be positioned respectively specifically includes:

identifying a plurality of readers-writers meeting a preset threshold condition of a wireless sensing network;

the multiple readers continuously acquire the signal intensity of the electronic tag to be positioned for preset times respectively;

selecting a median value of signal intensity data of each reader-writer continuously collected for a preset number of times as sampled signal intensity to obtain signal intensity data collected by a plurality of reader-writers, wherein the signal intensity data comprise signal intensities collected by the plurality of reader-writers to obtain the electronic tag.

As a preferred mode, obtaining distances between the electronic tag and the plurality of readers according to the logarithmic distance path loss model and the signal strength data specifically includes:

using logarithmic distance path loss modelCalculating the distances between the electronic tags and the plurality of readers-writers respectively, wherein,

p (d) is the signal strength when the distance between the reader and the electronic tag is d, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀The signal intensity of time, eta is an attenuation factor, sigma is an environmental influence factor, and xi is a zero-mean orthogonal distribution random variable with standard deviation of sigma.

Preferably, the obtaining a coarse positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle specifically includes:

according to the signal intensity data P ═ P received by N readers-writers₁ P₂…P_n]And the calculated corresponding distance D ═ D₁ d₂…d_n]；

According to the likelihood function of the obtained signal intensity P of the logarithmic distance path loss model:

when L (P | D) is maximum, the coarse positioning position of the electronic tag is obtained, namely

Wherein the content of the first and second substances,x and y are coordinates of the electronic tag, x_iAnd y_iCoordinates of N readers/writers, respectively, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀Signal strength in time, ξ represents an orthogonally distributed random variable with a standard deviation σ and a mean μ, η is an attenuation factor, l (P | (x, y) represents a function of each measurement point (x, y) with respect to the blind node signal strength P,the average value of the signal strength data received by the N readers.

Preferably, the modifying the environmental impact factor in the likelihood function through the environmental impact factor adjustment model specifically includes:

adjusting the model by the environmental impact factor:correcting an environment factor sigma in the likelihood function; wherein σ_i ⁿIs σ before adjustment_i，σ_i ⁿ⁺¹For corrected sigma_iWherein, in the step (A),d_ifor the mapping distance of the logarithmic distance path loss model,distance is calculated for the estimated coordinates, and η is the attenuation factor.

Further, the calculating the variance of the corrected environmental impact factor specifically includes:

by the formulaCalculating to obtain the variance sigma of the corrected environmental influence factor²Wherein σ₀ ²Is the initial environmental impact factor variance.

Preferably, when the variance meets a preset condition, obtaining an accurate position of the electronic tag according to the variance and the coarse positioning position specifically includes:

when the variance σ is²When the variance sigma is less than a preset environmental impact factor value²Substituting the rough positioning position to obtain the coordinate of the precise positioning position

As a preferable mode, the method further includes: and when the variance is not less than the preset environmental impact factor value, obtaining the rough positioning position of the electronic tag through the likelihood function and the maximum likelihood estimation principle again, correcting the environmental impact factor and recalculating the variance, judging the magnitude relation between the recalculated variance and the preset environmental impact factor value until the variance is less than the preset environmental impact factor value, and substituting the newly obtained variance into the newly obtained rough positioning position to obtain the accurate coordinate of the electronic tag.

The invention provides an indoor positioning method, which comprises the steps of respectively collecting signal intensity data of an electronic tag to be positioned through a plurality of readers; obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data; obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors; when the variance meets the preset condition, the accurate position of the electronic tag is obtained according to the variance and the coarse positioning position.

Drawings

Fig. 1 is a schematic flowchart of an indoor positioning method according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

An embodiment of the present invention provides an indoor positioning method, which is shown in fig. 1 and is a schematic flow chart of the indoor positioning method provided in the embodiment of the present invention, and the method includes steps S101 to S106:

s101, respectively acquiring signal intensity data of an electronic tag to be positioned through a plurality of readers;

s102, obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data;

s103, obtaining a coarse positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle;

s104, correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model;

s105, calculating the variance of the corrected environmental impact factors;

and S106, when the variance meets a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position.

When this embodiment is implemented specifically, when a certain person is positioned, signal intensity data acquisition is carried out to a certain electronic tag to be positioned simultaneously through a plurality of readers-writers, specifically: sending an intensity signal, and collecting signal intensity data reflected by the electronic tag;

the signal intensity received by the multipath channel generally conforms to logarithmic distribution, so the distances between the electronic tag and the plurality of readers can be obtained according to a logarithmic distance path loss model and the signal intensity data;

obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle;

since the environmental impact factors have a great influence on the positioning of the electronic tag positions, the environmental impact factors in the likelihood function need to be corrected by an environmental impact factor adjustment model

After correcting the environmental impact factors, calculating the variance of the corrected environmental impact factors;

and when the variance meets a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position.

The invention provides an indoor positioning method, which comprises the steps of respectively collecting signal intensity data of an electronic tag to be positioned through a plurality of readers; obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data; obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors; and when the variance meets a preset condition, obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position, and realizing accurate positioning through coarse positioning, correction factors, variance adjustment and environment influence factor judgment conditions based on a logarithmic distance path loss model.

In another embodiment of the present invention, the acquiring, by the plurality of readers, the signal intensity data of the electronic tag to be positioned respectively specifically includes:

identifying a plurality of readers-writers meeting a preset threshold condition of a wireless sensing network;

the multiple readers continuously acquire the signal intensity of the electronic tag to be positioned for preset times respectively;

selecting a median value of signal intensity data of each reader-writer continuously collected for a preset number of times as sampled signal intensity to obtain signal intensity data collected by a plurality of reader-writers, wherein the signal intensity data comprise signal intensities collected by the plurality of reader-writers to obtain the electronic tag.

In this embodiment, when a certain person is located, signal strength data acquisition is performed on an electronic tag to be located simultaneously by all readers that satisfy a certain threshold condition of the wireless sensor network, specifically: sending an intensity signal, and collecting signal intensity data reflected by the electronic tag;

it should be noted that the threshold condition may be signal strength or detection distance of the wireless sensor network;

the method comprises the steps that the initial acquisition of signal strength data has large errors, the positioning accuracy of the signal strength data is directly influenced, the signal strength data are continuously collected by the same reader-writer for N times by adopting median filtering, a middle value is selected as a signal strength sampling value of the reader-writer, the signal strength data comprise the signal strength sampling values of a plurality of samplers, wherein the specific value of the acquisition value N depends on the acquisition time and the positioning sensitivity, and can be specifically set according to actual conditions and can be set for 99 times.

By adopting a median filtering mode, the same reader-writer collects the position of the electronic tag for multiple times, and the median is taken as a sampling value, so that unstable factors during ranging can be avoided as much as possible, the unstable factors can accurately represent the transmission distance of the wireless sensing network, namely the accurate distance between the electronic tag and the reader-writer, and the positioning result is more accurate.

In another embodiment of the present invention, the obtaining the distances between the electronic tag and the plurality of readers according to the log distance path loss model and the signal strength data specifically includes:

using logarithmic distance path loss modelCalculating the distances between the electronic tags and the plurality of readers-writers respectively, wherein,

p (d) is the signal strength when the distance between the reader and the electronic tag is d, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀The signal intensity of time, eta is an attenuation factor, sigma is an environmental influence factor, and xi is a zero-mean orthogonal distribution random variable with standard deviation of sigma.

In this embodiment, when the embodiment is implemented specifically, the signal intensity data of the electronic tag collected by the multiple readers conforms to logarithmic distribution, and the relationship between the signal intensity and the distance is calculated by using a logarithmic distance path loss model, where the logarithmic distance path loss model specifically includes:

wherein P (d) is the signal strength when the distance between the reader and the electronic tag is d, d₀As a reference distance, P₀To readThe distance between the writer and the electronic tag is d₀The signal intensity of time, eta is an attenuation factor, sigma is an environmental influence factor, and xi is a zero-mean orthogonal distribution random variable with standard deviation of sigma.

It should be noted that, in practical applications, d is often taken₀The larger the value of the environmental impact factor σ, the larger the uncertainty of the logarithmic distance path loss model is at 1 m.

The distance between the acquired signal intensity data and the distance between the tag data and the reader-writer are represented by a logarithmic distance path loss model with logarithmic distribution, so that the characteristics of a wireless signal propagation path are better met, and the positioning error caused by a positioning algorithm is reduced.

In another embodiment of the present invention, the obtaining a coarse positioning position of the electronic tag according to distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle specifically includes:

according to the signal intensity data P ═ P received by N readers-writers₁ P₂…P_n]And the calculated corresponding distance D ═ D₁ d₂…d_n]；

According to the likelihood function of the obtained signal intensity P of the logarithmic distance path loss model:

when L (P | D) is maximum, the coarse positioning position of the electronic tag is obtained, namely

Wherein the content of the first and second substances,x and y are coordinates of the electronic tag, x_iAnd y_iFor N reads respectivelyCoordinates of the writer, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀Signal strength in time, ξ represents an orthogonally distributed random variable with a standard deviation σ and a mean μ, η is an attenuation factor, l (P | (x, y) represents a function of each measurement point (x, y) with respect to the blind node signal strength P,the average value of the signal strength data received by the N readers.

In this embodiment, let N reader-writers receive signal strength data P ═ P₁ P₂…P_n]And the calculated corresponding distance D ═ D₁ d₂…d_n]；

The likelihood function of the signal strength data P obtained from the log-range path loss model is:

when L (P | D) is maximum, the coarse positioning position of the electronic tag is obtained, namely

Wherein the content of the first and second substances,x and y are coordinates of the electronic tag, x_iAnd y_iCoordinates of N readers/writers, respectively, d₀As a reference distance, P₀The distance between the reader-writer and the electronic tag is d₀Signal strength in time, ξ represents an orthogonally distributed random variable with a standard deviation σ and a mean μ, η is an attenuation factor, l (P | (x, y) represents a function of each measurement point (x, y) with respect to the blind node signal strength P,the average value of the signal strength data received by the N readers.

And simulating through a likelihood function according to the obtained signal strength and corresponding position relation of the electronic tag and the reader-writer, wherein the x and y positions of the likelihood function are the positions of rough positioning under the condition of a peak value according to the maximum likelihood estimation principle. And the primary positioning of the electronic tag is realized.

In another embodiment provided by the present invention, the modifying the environmental impact factor in the likelihood function by the environmental impact factor adjustment model specifically includes:

adjusting the model by the environmental impact factor:correcting an environment factor sigma in the likelihood function; wherein σ_i ⁿIs σ before adjustment_i，σ_i ⁿ⁺¹For corrected sigma_iWherein, in the step (A),d_ifor the mapping distance of the logarithmic distance path loss model,distance is calculated for the estimated coordinates, and η is the attenuation factor.

When the embodiment is specifically implemented, the environment influence factor in the likelihood function is corrected through the environment influence factor adjustment model, and the accuracy of the log-range path loss model can be influenced by the value of the environment influence factor sigma, so that a subsequent positioning result based on the log-range path loss model is greatly influenced, and the accuracy of positioning can be greatly improved by correcting the environment influence factor.

In another embodiment provided by the present invention, the calculating the variance of the corrected environmental impact factor specifically includes:

by the formulaCalculating to obtain the variance sigma of the corrected environmental influence factor²Wherein σ₀ ²Is the initial environmental impact factor variance.

In the embodiment, the formula is usedCalculating to obtain the variance sigma of the corrected environmental influence factor²Wherein σ₀ ²Is the initial environmental impact factor variance.

In another embodiment provided by the present invention, the obtaining the accurate position of the electronic tag according to the variance and the coarse positioning position when the variance meets a preset condition specifically includes:

when the variance σ is²When the variance sigma is less than a preset environmental impact factor value²Substituting the rough positioning position to obtain the coordinate of the precise positioning position

It should be noted that the preset environmental impact factor value may be artificially set according to the characteristics of the specific indoor location, and the purpose of the preset environmental impact factor value is to limit the influence degree of the environmental impact factor on the measurement accuracy in the actual measurement within a controllable range.

In the specific implementation of this embodiment, the variance and the preset value of the environmental impact factor are determined, and only when the variance is smaller than the preset value of the environmental factor, it is indicated that the corrected value of the environmental impact factor meets the preset precision condition, and the normalized control of the measurement precision is realized through the accurate positioning position obtained by calculation.

In another embodiment provided by the present invention, the method further comprises: and when the variance is not less than the preset environmental impact factor value, obtaining the rough positioning position of the electronic tag through the likelihood function and the maximum likelihood estimation principle again, correcting the environmental impact factor and recalculating the variance, judging the magnitude relation between the recalculated variance and the preset environmental impact factor value until the variance is less than the preset environmental impact factor value, and substituting the newly obtained variance into the newly obtained rough positioning position to obtain the accurate coordinate of the electronic tag.

When the method is implemented specifically, signal intensity data of the electronic tag to be positioned are collected through a plurality of readers; obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data; obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors;

judging the variance of the corrected environmental factor and the value of the environmental influence factor, and when the variance sigma is larger than the threshold value²When the environmental impact factor value is not less than the environmental impact factor value, the rough positioning position of the electronic tag is obtained through a likelihood function and a maximum likelihood estimation principle according to the distances between the electronic tag and the plurality of readers; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors; judging the variance of the corrected environmental factor and the value of the environmental influence factor again until the variance sigma²Less than the value of the environmental impact factor, the variance σ is set²Substituting the newly obtained coarse positioning position to obtain the precise positioning position coordinate

The variance of the corrected environmental impact factors is compared with the preset environmental impact factors, and accurate positioning is limited to be carried out until the environmental impact factors are smaller than the preset value, so that the interference of the environmental factors to a positioning algorithm is in a controllable range, and the positioning accuracy is improved.

The invention provides an indoor positioning method, which comprises the steps of respectively collecting signal intensity data of an electronic tag to be positioned through a plurality of readers; obtaining the distances between the electronic tag and the plurality of readers according to a logarithmic distance path loss model and the signal intensity data; obtaining a rough positioning position of the electronic tag according to the distances between the electronic tag and the plurality of readers and through a likelihood function and a maximum likelihood estimation principle; correcting the environmental influence factors in the likelihood function through an environmental influence factor adjustment model; calculating the variance of the corrected environmental impact factors; when the variance meets the preset condition, the accurate position of the electronic tag is obtained according to the variance and the coarse positioning position.

It should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations are also regarded as the protection scope of the present invention.