CN107122810A - A kind of label authentic authentication method based on RFID physical layer feature - Google Patents
A kind of label authentic authentication method based on RFID physical layer feature Download PDFInfo
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
The invention discloses a kind of label authentic authentication method based on RFID physical layer feature, including：Two passive type RFID tags are disposed, label pair is constituted；Build authentication region；In authentication region, obtain label pair and the signal of communication section of RFID reader is used as a training sample；From multiple samples, composing training sample set carries out the extraction of feature to training sample set；During test sample, using identical feature extraction mode；The region that the characteristic value of test sample and training sample is constituted with time shaft is calculated respectively, come discriminating test sample whether is same a pair of tag with training sample using the Duplication between region.If region Duplication is more than threshold value, it is determined as it being same label pair, otherwise, it is determined that it not is same label pair to be.By judging whether it is to belong to same label pair, to identify whether as same object；Changeable, and the influence that noise is caused to identification object prevented due to environment of the invention effective, adds the robustness of system.
Description
Technical field
The invention belongs to radio frequency identification (RFID) technical field category, and in particular to one kind is special based on RFID physical layer
The label authentic authentication method levied
Background technology
REID is in the monitoring, tracing management of logistics management now, goods and dangerous material, the luggage support of civil aviaton
There is quite ripe application in terms of fortune.Other identification technologies such as REID and Quick Response Code, bar code are compared, excellent
Point is essentially consisted in：(1) both can be using the self-contained information of label, it is convenient label information can also to be carried out using reader
Change.(2) can read write tag at a distance, and multiple labels can be recognized simultaneously, its information storage is big, and data safety can
Reuse.
The principle of REID is the radio sent using the specific RF tag (RFID Tags) of sensing identification
The energy of ripple special frequency channel, or the signal of a certain frequency is actively sent by electronic tag, contactless two-way communication is carried out, is completed
Target identification and data switching purpose.RF tag is product electronic code (EPC) physical support, is attached to traceable thing
On product and it can be identified and read and write.
In common logistics management and item tracing management, the unique of RF tag electronic code (EPC) is frequently utilized that
Property come false proof and follow the trail of, its principle is：RF tag is attached on article, makes it article inalienable part.
When RF tag " being forced " is separated with article, " integrality " of article is destroyed, and article is considered as false proof end.In above-mentioned ring
In section, fake producer, which may destroy, to carry out camouflage articles using identical EPC forgery RF tag after article and is not affected by infringement.At present
Usually used label anti-counterfeit technological means is perfect not enough, is limited by application environment factors, fails effectively to make
The behavior only palmed off.Therefore, the label authentic authentication method based on RFID physical layer feature, tool is of great significance and made
With.
The content of the invention
It is an object of the invention to overcome shortcoming present in above-mentioned prior art, propose a kind of special based on RFID physical layer
The label authentic authentication method levied, overcomes identical EPC forgery RF tag to be difficult to the difficulty being noticeable, and with accurate
Height, the low advantage of cost.
A kind of label authentic authentication method based on RFID physical layer feature, this method is applied to the article of logistics transportation
On, comprise the following steps：
Step 1, two passive type RFID tags are disposed in an article surface, constitutes label pair；
Step 2, authentication region is built, the authentication region includes label to, RFID reader and audiomonitor, the prison
Equipment is listened while the signal that signal and label return RFID reader to backscattering that sends of RFID reader can be received；
Step 31, in authentication region, the communication of RFID reader and label pair is monitored by audiomonitor in time T
Signal, obtains the physical layer information of the signal of communication in time T；
Step 32, the order of RFID reader transmission, interception RFID reader hair are parsed from the physical layer information
Signal between the order ACK and QUERY/QREP/QADJ sent, obtains EPC signal segments；
Step 33, EPC signal segments step 32 obtained carry out FFT, obtain the EPC signal segments after FFT, choose after FFT
Signal segment of the EPC signal segments in [TL, TH] interval as selection EPC signal segments, using clustering algorithm by the EPC of selection
The EPC signal segments of two RFID tags are separated in signal segment, obtain two EPC signal segments；Wherein, TH>TL>0；
Step 34, if two RFID tags are respectively label 1 and label 2, it will be chosen in the EPC signal segments of label 1 from EPC
N number of data of starting point to n-th data are used as signal segment P1, will be chosen in the EPC signal segments of label 2 from EPC starting point to n-th
N number of data of data are used as signal segment P2, difference signal section S is obtained by formula (1)：
si=p2i-p1i
S=[s1,s2,…,si,…,sN] (1)
In formula (1), i ∈ [1, N]；N is the integer more than 1；P1=[p11,p12,…,p1i,…,p1N]；P2=[p21,
p22,…p2i,…,p2N]；
Step 35, difference signal section S is carried out after FFT, then by low pass filter, the difference signal after being handled
Section, the sampled point a in the difference signal section after processing to b intervals is normalized, b ＞ a, b ∈ [1, N], a ∈ [1,
N], the signal segment after being normalized；
Step 36, if the signal segment after normalization is S ＇, S ＇ are regard as a training sample；
Wherein, s '=[s1′,...,sj′,...,sn'], n=b-a+1；
Repeat step 31~35L times, chooses M training sample and is used as training sample set Train；
Step 37, the characteristic value collection of training sample set is obtained by formula (2)
Sm＇=[s ＇m1..., s ＇mj..., s ＇mn], n=b-a+1, m ∈ [1, M]
In formula (2), S ＇mRepresent the signal segment of m-th of training sample in training sample set Train, s ＇ijFor i-th of training
The amplitude of j-th of sampled point signal in the signal segment of sample；
Step 41, optionally any label is to as test label pair, by the test label to being put into the certification that step 2 is built
In region；
Step 421, in authentication region, RFID reader and test label pair are monitored by audiomonitor in time T
Signal of communication, obtain time T in signal of communication physical layer information；
Step 422, the order of RFID reader transmission, interception RFID reader hair are parsed from the physical layer information
Signal between the order ACK and QUERY/QREP/QADJ sent, obtains testing EPC signal segments；
Step 423, test EPC signal segments step 422 obtained carry out FFT, obtain the test EPC signal segments after FFT,
Signal segment of the test EPC signal segments after FFT in [TL, TH] interval is chosen as the test EPC signal segments of selection, using poly-
Class algorithm separates the EPC signal segments of two test RFID tags in the test EPC signal segments of selection, obtains two test EPC
Signal segment；Wherein, TH>TL>0；
Step 424, if two test RFID tags are respectively test label 1 and test label 2, by the survey of test label 1
N number of data from EPC starting points to n-th data are chosen in examination EPC signal segments as test signal section p1', by the EPC of label 2
N number of data from EPC starting points to n-th data are chosen in signal segment as signal segment p2', obtain testing difference by formula (3)
Signal segment T：
Ti=p ＇2i- p ＇1i
T=[T1,T2,…,Ti,…sN] (3)
In formula (3), i ∈ [1, N]；N is the integer more than 1；p1'=[p ＇11, p ＇12..., p ＇1i..., p ＇1N]；p2'=
[p ＇21, p ＇22..., p ＇2i..., p ＇2N]；
Step 425, test difference signal section T is carried out after FFT, then carries out LPF, the test after being handled is poor
Value signal section, the sampled point a in the test difference signal section after processing to b intervals is normalized, b ＞ a, b ∈ [1,
N], a ∈ [1, N], the test signal section T ＇ after being normalized；
Wherein, T '=[T1′,...,Tj′,...,Tn'], n=b-a+1；
Step 43, by formula (4) obtain T ＇ withRegion Duplication R：
In formula (4), A (T ＇) represents signal segment T ＇ and time shaft area defined,Represent signal segmentWith
Time shaft area defined；
Step 44, if region Duplication is more than threshold value TH, 0≤TH≤1 is then determined as it being same label pair, otherwise, it is determined that
Not to be same label pair.
Further, the clustering algorithm in the step 33 is K-means algorithms, and the utilization K-means algorithms will be selected
The EPC signal segments of two RFID tags separately include in the EPC signal segments taken：
The average and covariance for the EPC signal segments chosen are calculated, the average and covariance is regard as K-means algorithms
Input, 2 are set to by the k values in K-means algorithms.
Compared with prior art, the present invention has following technique effect：
The present invention to recognizing object, can effectively prevent changeable due to environment using label, and noise is to knowledge
The influence that other object is caused, adds the robustness of system.Moreover, single tag recognition object safety coefficient is not high, Ke Yitong
Cross and forged using identical ID label.The present invention can effectively refuse this phenomenon, the safety of larger raising system
Property, and be difficult to be forged imitation.
Brief description of the drawings
Fig. 1 is flow chart of the invention；
Fig. 2 is system deployment schematic diagram of the invention；
Fig. 3 is same label to the design sketch after signal normalization under various circumstances；
Fig. 4 is different labels to the design sketch after the signal normalization under same environment.
Embodiment
Explanation is further explained to the present invention with reference to the accompanying drawings and examples.
Embodiment 1
A kind of label authentic authentication method based on RFID physical layer feature is present embodiments provided, is comprised the following steps：
Step 1, two passive type RFID tags are disposed on an article, label pair is constituted；
Step 2, as shown in Fig. 2 building authentication region, the authentication region includes label to, RFID reader and monitoring
Equipment, the transmission signal and label that the audiomonitor can receive RFID reader simultaneously returns RFID reader to backscattering
Signal；
Step 31, in authentication region, the communication of RFID reader and label pair is monitored by audiomonitor in time T
Signal, obtains the physical layer information of the signal of communication in time T；
T takes 3 seconds in the present embodiment.
RFID reader antenna transmission signal, label is set to replying RFID reader, monitoring by way of backscattering
It is standby to monitor RFID reader and the communication process of label pair.The antenna of RFID reader and audiomonitor is all using the side for determining frequency
Formula, and the frequency of audiomonitor is consistent with the frequency that RFID reader is set.The putting position requirement of the antenna of audiomonitor can
To receive the signal that signal and label return RFID reader to backscattering that sends of RFID reader simultaneously.
Step 32, the order of RFID reader transmission, interception RFID reader hair are parsed from the physical layer information
Signal between the order ACK and QUERY/QREP/QADJ sent, obtains EPC signal segments；
Step 33, EPC signal segments step 32 obtained carry out FFT, obtain the EPC signal segments after FFT, choose after FFT
EPC signal segments [800,8000] interval in signal segment as selection EPC signal segments, using K-means algorithms will select
The EPC signal segments of two RFID tags are separated in the EPC signal segments taken, obtain two EPC signal segments；
The EPC signal segments of two RFID tags in the EPC signal segments of selection are separated using K-means in the step 33
Including：
Sample frequency is set as 10M, the average and covariance of the EPC signal segments chosen are calculated, by the average and association side
The poor input as K-means algorithms；K values in K-means algorithms are set to 2.
K-means algorithms are in document " big algorithm [M] Beijing of Xindong Wu, Vipin Kumar. data minings ten：Clearly
Magnificent university press .2014:There is detailed introduction in 19-30. ".
Step 34, if two RFID tags are respectively label 1 and label 2, it will be chosen in the EPC signal segments of label 1 from EPC
N number of data of starting point to n-th data are used as signal segment P1, will be chosen in the EPC signal segments of label 2 from EPC starting point to n-th
N number of data of data are used as signal segment P2, difference signal section S is obtained by formula (1)：
si=p2i-p1i
S=[s1,s2,…,si,…,sN] (1)
In formula (1), i ∈ [1, N]；P1=[p11,p12,…,p1i,…,p1N]；P2=[p21,p22,…p2i,…,p2N]；
In the present embodiment, N takes 8000；
Step 35, difference signal section S is carried out after FFT, then by low pass filter, the difference signal after being handled
Section, the sampled point a in the difference signal section after processing to b intervals is normalized, b ＞ a, b ∈ [1, N], a ∈ [1,
N], the signal segment after being normalized；
Step 36, if the signal segment after normalization is S ＇, S ＇ are regard as a training sample；
Wherein, s '=[s1′,...,sj′,...,sn'], n=b-a+1；
In the present embodiment, a=50, b=1000；
Repeat step 31~35L times, chooses M training sample and is used as training sample set Train；
Step 37, the characteristic value collection of training sample set is obtained by formula (2)
Sm＇=[s ＇m1 ..., s ＇mj..., s ＇mn], n=b-a+1, m ∈ [1, M]
In formula (2), Sm＇ represents the signal segment of m-th of training sample in training sample set Train, s ＇ijFor i-th of training
The amplitude of j-th of sampled point signal in the signal segment of sample；
Step 421, in authentication region, RFID reader and test label pair are monitored by audiomonitor in time T
Signal of communication, obtain time T in signal of communication physical layer information；
Step 422, the order of RFID reader transmission, interception RFID reader hair are parsed from the physical layer information
Signal between the order ACK and QUERY/QREP/QADJ sent, obtains testing EPC signal segments；
Step 423, test EPC signal segments step 422 obtained carry out FFT, obtain the test EPC signal segments after FFT,
Signal segment of the test EPC signal segments after FFT in [800,8000] interval is chosen as the test EPC signal segments of selection, profit
The EPC signal segments of two test RFID tags in the test EPC signal segments of selection are separated with K-means algorithms, two are obtained
Test EPC signal segments；
K-means is utilized in the step 423 by the EPC signals of two RFID tags in the test EPC signal segments of selection
Section separately includes：
Sample frequency is set as 10M, calculate choose test EPC signal segments average and covariance, by the average with
Covariance as K-means algorithms input；K values in K-means algorithms are set to 2.
K-means algorithms are in document " big algorithm [M] Beijing of Xindong Wu, Vipin Kumar. data minings ten：Clearly
Magnificent university press .2014:There is detailed introduction in 19-30. ".
Step 424, if two test RFID tags are respectively test label 1 and test label 2, by the survey of test label 1
N number of data from EPC starting points to n-th data are chosen in examination EPC signal segments as test signal section p1', by the EPC of label 2
N number of data from EPC starting points to n-th data are chosen in signal segment as signal segment p2', obtain testing difference by formula (3)
Signal segment T：
Ti=p '2i-p′1i
T=[T1,T2,…,Ti,…sN] (3)
In formula (3), i ∈ [1, N]；N is the integer more than 1；p1'=[p '11,p′12,...,p′1i,...,p′1N]；p2'=
[p′21,p′22,...,p′2i,...,p′2N]；
In the present embodiment, N takes 8000；
Step 425, test difference signal section T is carried out after FFT, then carries out LPF, the test after being handled is poor
Value signal section, the sampled point a in the test difference signal section after processing to b intervals is normalized, b ＞ a, b ∈ [1,
N], a ∈ [1, N], the test signal section T ＇ after being normalized；
Wherein, T '=[T1′,...,Tj′,...,Tn'], n=b-a+1；
In the present embodiment, a=50, b=1000；
Step 43, by formula (4) obtain T ＇ withRegion Duplication R：
In formula (4), A (T ＇) represents signal segment T ＇ and time shaft area defined,Represent signal segmentWith
Time shaft area defined；
The present embodiment calculate A (T ＇) andThe numerical integration method based on trapezoidal rule is used, such as formula
(5)；
In formula (5), B represents signal segment, value be T ＇ or[a, b] represents signal segment B sampled point, n=b-a, and h is
Step-length, is set to 1.A represents signal segment B and time shaft area defined area, when even B values are T ＇, and A is A (T ＇)；If
B values areWhen, A is
Step 44, if region Duplication is more than threshold value TH, 0≤TH≤1 is then determined as it being same label pair, otherwise, it is determined that
Not to be same label pair.
Experimental result
If it is determined that being same label pair, such as Fig. 3, the region that signal segment and the time shaft of same label pair are constituted is weighed substantially
Close, region Duplication be 0.9544 be more than threshold value TH, be determined as same label pair, in the method, the threshold value TH that we take
For 0.77.
If it is determined that for different labels pair, such as Fig. 4, label to 1 the region that is constituted with time shaft of signal segment with label to 2
Signal segment compared with the region that time shaft is constituted, region Duplication be 0.6223 be less than threshold value 0.77, be determined as it not being same
One label pair.
Claims (2)
1. a kind of label authentic authentication method based on RFID physical layer feature, this method is applied on the article of logistics transportation,
It is characterised in that it includes following steps：
Step 1, two passive type RFID tags are disposed in an article surface, constitutes label pair；
Step 2, authentication region is built, the authentication region includes label to, RFID reader and audiomonitor, and the monitoring is set
It is standby to receive the signal that signal and label return RFID reader to backscattering that sends of RFID reader simultaneously；
Step 31, in authentication region, the communication for monitoring RFID reader and label pair by audiomonitor in time T is believed
Number, obtain the physical layer information of the signal of communication in time T；
Step 32, the order of RFID reader transmission is parsed from the physical layer information, interception RFID reader is sent
The signal between ACK and QUERY/QREP/QADJ is ordered, EPC signal segments are obtained；
Step 33, EPC signal segments step 32 obtained carry out FFT, obtain the EPC signal segments after FFT, choose the EPC after FFT
Signal segment of the signal segment in [TL, TH] interval as selection EPC signal segments, using clustering algorithm by the EPC signals of selection
The EPC signal segments of two RFID tags are separated in section, obtain two EPC signal segments；Wherein, TH>TL>0；
Step 34, if two RFID tags are respectively label 1 and label 2, it will be chosen in the EPC signal segments of label 1 from EPC starting points
N number of data to n-th data are used as signal segment P1, will be chosen in the EPC signal segments of label 2 from EPC starting points to n-th data
N number of data be used as signal segment P2, difference signal section S is obtained by formula (1)：
si=p2i-p1i
S=[s1,s2,…,si,…,sN] (1)
In formula (1), i ∈ [1, N]；N is the integer more than 1；P1=[p11,p12,…,p1i,…,p1N]；P2=[p21,p22,…
p2i,…,p2N]；
Step 35, difference signal section S is carried out after FFT, then by low pass filter, the difference signal section after being handled is right
The sampled point a in difference signal section after processing is normalized to b intervals, and b ＞ a, b ∈ [1, N], a ∈ [1, N] are obtained
Signal segment after to normalization；
Step 36, if the signal segment after normalization is S ＇, S ＇ are regard as a training sample；
Wherein, s '=[s1′,...,sj′,...,sn'], n=b-a+1；
Repeat step 31~35L times, chooses M training sample and is used as training sample set Train；
Step 37, the characteristic value collection of training sample set is obtained by formula (2)
S ＇m=[s ＇m1..., s ＇mj..., s ＇mn], n=b-a+1, m ∈ [1, M]
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In formula (2), S ＇mRepresent the signal segment of m-th of training sample in training sample set Train, s ＇ijFor i-th of training sample
Signal segment in j-th of sampled point signal amplitude；
Step 41, optionally any label is to as test label pair, by the test label to being put into the authentication region that step 2 is built
In；
Step 421, in authentication region, RFID reader and test label are monitored to leading to by audiomonitor in time T
Believe signal, obtain the physical layer information of the signal of communication in time T；
Step 422, the order of RFID reader transmission is parsed from the physical layer information, interception RFID reader is sent
The signal between ACK and QUERY/QREP/QADJ is ordered, obtains testing EPC signal segments；
Step 423, test EPC signal segments step 422 obtained carry out FFT, obtain the test EPC signal segments after FFT, choose
Signal segment of the test EPC signal segments in [TL, TH] interval after FFT is calculated as the test EPC signal segments of selection using cluster
Method separates the EPC signal segments of two test RFID tags in the test EPC signal segments of selection, obtains two test EPC signals
Section；Wherein, TH>TL>0；
Step 424, if two test RFID tags are respectively test label 1 and test label 2, by the test EPC of test label 1
N number of data from EPC starting points to n-th data are chosen in signal segment as test signal section p1', by the EPC signal segments of label 2
N number of data of the middle selection from EPC starting points to n-th data are used as signal segment p2', test difference signal section is obtained by formula (3)
T：
Ti=p ＇2i- p ＇1i
T=[T1,T2,…,Ti,…sN] (3)
In formula (3), i ∈ [1, N]；N is the integer more than 1；P ＇1=[p ＇11, p ＇12..., p ＇1i..., p ＇1N]；P ＇2=
[p ＇21, p ＇22..., p ＇2i..., p ＇2N]；
Step 425, test difference signal section T is carried out after FFT, then carries out LPF, the test difference letter after being handled
Number section, the sampled point a in the test difference signal section after processing to b intervals is normalized, b ＞ a, b ∈ [1, N], a
∈ [1, N], the test signal section T ＇ after being normalized；
Wherein, T '=[T1＇ ..., Tj′,...,Tn'], n=b-a+1；
Step 43, by formula (4) obtain T ＇ withRegion Duplication R：
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<mrow>
<mo>(</mo>
<msup>
<mi>T</mi>
<mo>&prime;</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>&cap;</mo>
<mi>A</mi>
<mrow>
<mo>(</mo>
<mover>
<msup>
<mi>S</mi>
<mo>&prime;</mo>
</msup>
<mo>&OverBar;</mo>
</mover>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>A</mi>
<mrow>
<mo>(</mo>
<msup>
<mi>T</mi>
<mo>&prime;</mo>
</msup>
<mo>)</mo>
</mrow>
<mo>&cup;</mo>
<mi>A</mi>
<mrow>
<mo>(</mo>
<mover>
<msup>
<mi>S</mi>
<mo>&prime;</mo>
</msup>
<mo>&OverBar;</mo>
</mover>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (4), A (T ＇) represents signal segment T ＇ and time shaft area defined,Represent signal segmentAnd time shaft
Area defined；
Step 44, if region Duplication is more than threshold value TH, 0≤TH≤1 is then determined as it being same label pair, otherwise, it is determined that for not
It is same label pair.
2. the label authentic authentication method as claimed in claim 1 based on RFID physical layer feature, it is characterised in that the step
Clustering algorithm in rapid 33 is K-means algorithms, and the utilization K-means algorithms are by two RFID in the EPC signal segments of selection
The EPC signal segments of label separately include：
The average and covariance for the EPC signal segments chosen are calculated, the average and covariance is regard as the defeated of K-means algorithms
Enter, the k values in K-means algorithms are set to 2.
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| WO2019061515A1 (en) * | 2017-09-30 | 2019-04-04 | 深圳大学 | Robust wireless communication physical layer slope authentication method and device |
| CN116185959A (en) * | 2023-04-28 | 2023-05-30 | 公安部信息通信中心 | Superimposed tag recognition and processing system |
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| US20070194889A1 (en) * | 2006-02-03 | 2007-08-23 | Bailey Daniel V | Security Provision in Standards-Compliant RFID Systems |
| CN102411748A (en) * | 2011-07-28 | 2012-04-11 | 黄晋 | Safety anti-counterfeiting system and method based on two wireless radio frequency tags |
| CN106056339A (en) * | 2016-06-02 | 2016-10-26 | 王鸽 | Object identification method utilizing penetrability of electromagnetic wave |
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| US20070194889A1 (en) * | 2006-02-03 | 2007-08-23 | Bailey Daniel V | Security Provision in Standards-Compliant RFID Systems |
| CN102411748A (en) * | 2011-07-28 | 2012-04-11 | 黄晋 | Safety anti-counterfeiting system and method based on two wireless radio frequency tags |
| CN106056339A (en) * | 2016-06-02 | 2016-10-26 | 王鸽 | Object identification method utilizing penetrability of electromagnetic wave |
| CN106066977A (en) * | 2016-06-12 | 2016-11-02 | 西安交通大学 | A kind of label two dimension method for sequencing utilizing object to move |
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| WO2019061515A1 (en) * | 2017-09-30 | 2019-04-04 | 深圳大学 | Robust wireless communication physical layer slope authentication method and device |
| CN116185959A (en) * | 2023-04-28 | 2023-05-30 | 公安部信息通信中心 | Superimposed tag recognition and processing system |
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