CN104765016A - Radio frequency identification and location method based on intelligent control over power - Google Patents
Radio frequency identification and location method based on intelligent control over power Download PDFInfo
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- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/0008—General problems related to the reading of electronic memory record carriers, independent of its reading method, e.g. power transfer
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Abstract
The invention belongs to the technical field of mobile communication, and relates to a radio frequency identification and location method based on intelligent control over power. According to the method, the power of each reader is set into two transmitting modes of coarse-grained radiation and fine-grained radiation, a power energy level mapping function is set up, mapping from the coarse-grained radiation mode to the fine-grained radiation mode within the minimum effective energy level range is achieved, a fine-grained location radiation power sequence is generated to intelligently control the power of the readers, identity cognition sequences of labels to be located in the coarse-grained radiation mode and the fine-grained radiation mode are compared to detect whether the labels to be located are transferred out of a location environment or enter a dead zone, and neighbor reference label cognition sequences of the coarse-grained radiation mode and the fine-grained radiation mode are compared to detect whether path loss characteristics change or not. By improving the power transmitting mode of the existing radio frequency readers, the location efficiency and the location real-time performance can be effectively improved.
Description
Technical field
The invention belongs to RF wireless communication technology field, relate to a kind of frequency recognition positiming method controlled based on power intelligent.
Background technology
By means of noncontact, non line of sight, certification without the need to manual intervention, support the advantages such as many tag recognition operation, based on radio-frequency (RF) identification (Radio Frequency Identification, RFID) technology indoor passive location technology extensively and the field such as logistics, industry manufacture, medical and amusement and recreation.
At present, based on the indoor passive positioning system of RFID mainly based on LANDMARC algorithm, the off-line data of reader is substituted by introducing reference label motion capture environmental information, adopt typical field intensity Euclidean distance to choose neighbour's reference label, introduce the positional information that typical residual weighting algorithm obtains label to be positioned.Compared to other location algorithms, LANDMARC algorithm not only reduces system cost, improve the adaptive capacity to environment of system, and precision is good.However, LANDMARC location real-time characteristic on still there are some defects, mainly because:
(1) arithmetic accuracy is limited by reference label layout density.Reference label is laid more intensive, and positioning precision is higher, but too much reference label laying not only increases cost, also can cause collision and interference between extra label.
(2) arithmetic accuracy is limited by the maximum transmission power energy level of reader.Typical reader obtains the collection of letters intensity instruction of each label by the mode progressively reducing emissive power energy level, and emissive power energy level is larger, and the read-write scope of reader is larger, and the label of reading is more.Dimension, promotes maximum transmission power energy level, can strengthen reader to the judgement ability of signal intensity and parsing degree, but single emission power levels poll can be caused consuming time longer, affect location efficiency.
To sum up, study and optimize the power emission mode of reader, for the real-time characteristic improving radio-frequency (RF) identification positioning system, the research and practice meaning that pole has tool important, but correlative study is still in the starting stage.
Summary of the invention
The problem that the present invention need solve is to provide a kind of frequency recognition positiming method controlled based on power intelligent.
Based on the method, existing radio-frequency (RF) identification positioning system, under the prerequisite ensureing positioning precision, reduces system power dissipation, rejects unnecessary reference label, suppress the read-write between many labels to be collided, effectively promote location efficiency.
1, based on the frequency recognition positiming method that power intelligent controls, comprise the following steps:
Step 1: setting reader adopts coarseness radiation and fine granularity radiation two kinds of power emission modes;
Step 2: consider the path loss difference characteristic of different chamber's inner position environment, the layout density of reference label and the requirement of positioning precision and real-time, the power grade set of setting coarseness and fine granularity radiation.
Step 3: arrange multiple test point in indoor positioning environment, adopts nonlinear fitting mode to set up power levels mapping function.
Step 4: each reader arranged in localizing environment is coarseness Radiation work mode, the mode adopting emissive power energy level to successively decrease step by step from big to small carries out quick position, generates the cognitive sequence of tag identity coarseness to be positioned according to Monte Carlo method.
Step 5: for each label to be positioned, all sets up the minimum effective energy level scope of its coarseness;
Step 6: for each label to be positioned, records the neighbour's reference label within the scope of the minimum effective energy level of its coarseness, and generates the cognitive sequence of neighbour's reference label coarseness.
Step 7: according to power levels mapping function, map out the minimum effective energy level scope of fine granularity that the minimum effective energy level scope of coarseness of each label to be positioned is corresponding.
Step 8: union operation is carried out to whole elements of the minimum effective energy level scope of the fine granularity of whole label to be positioned, and by arranging from big to small, generate the fine granularity location radiation power sequence of reader.
Step 9: each reader in localizing environment is set to fine granularity Radiation work mode, according to fine granularity location radiation power sequence, arrive greatly little mode of successively decreasing step by step by reader emissive power to carry out fine granularity and accurately locate, generate the cognitive sequence of tag identity fine granularity to be positioned according to Monte Carlo method.
Step 10: for each label to be positioned, records the neighbour's reference label within the scope of the minimum effective energy level of its fine granularity, and generates the cognitive sequence of neighbour's reference label fine granularity.
Step 11: arrange loop cycle scan mechanism and perform fine granularity location, according to Monte Carlo mode, upgrades the cognitive sequence of neighbour's reference label fine granularity of each label to be positioned.
Step 12: adopt LANDMARC algorithm, obtain the positional information of label to be positioned.
Step 13: the cognitive coarseness sequence of tag identity more to be positioned and the cognitive fine granularity sequence of tag identity to be positioned, if the element number of fine granularity sequence is less than the element number of coarseness sequence, now return step 4, carry out coarseness quick position.
Step 14: the cognitive sequence of neighbour's reference label fine granularity of more each label and the cognitive sequence of neighbour's reference label coarseness, if S when the two difference is greater than certain predetermined threshold value
r, now return step 3, reset power levels mapping function M{}.
Step 15: for the label newly-increased to be positioned in localizing environment, arrange timing cycle scan mechanism, makes each reader perform coarseness radiation mode, upgrades the cognitive coarseness sequence of tag identity to be positioned.
Step 16: judge whether positioning result reaches set accuracy requirement, if meet set constraint condition, then close reader, terminate this position fixing process.
Accompanying drawing illustrates:
fig. 1it is flow chart element of the present invention
figure;
fig. 2it is indoor environment of the present invention signal
figure.
Embodiment:
Purport of the present invention proposes a kind of frequency recognition positiming method controlled based on power intelligent, the method adopts LANDMARC location algorithm, by controlling reader Radiation work mode, effective control reader maximum transmission power energy level, to the reading of label, improves the real-time characteristic of location efficiency and positioning system.
Below in conjunction with
accompanying drawing 1embodiment of the present invention is described further in detail.
The present invention relates to LANDMARC algorithm, location scene cloth is set to
as Fig. 2shown localizing environment.Complete implementation process in the following manner.
Consider the path loss difference characteristic of different chamber's inner position environment, the layout density of reference label and the requirement of positioning precision and real-time, setting reader adopts coarseness radiation and fine granularity radiation two kinds of power emission modes, and the power grade set of setting coarseness radiation is
the power grade set of fine granularity radiation is
α and β represents the number of coarseness and each grade of fine granularity respectively.
Multiple test point is set in indoor positioning environment, adopts nonlinear fitting mode to set up power levels mapping function M{}, for arbitrary power grade of coarseness radiation
all map out fine granularity radiation power energy level corresponding with it
each reader in localizing environment is set to coarseness Radiation work mode, and the mode adopting emissive power energy level to successively decrease step by step from big to small carries out quick position, according to Monte Carlo mode, generates the cognitive sequence of tag identity coarseness to be positioned
n represents positioning label sequence number,
96 EPC information of i-th label to be positioned.
For arbitrary label to be positioned, all set up the minimum effective energy level scope of its coarseness, the minimum effective energy level scope of the coarseness as i-th label to be positioned is
namely when the emissive power energy level of each reader is
time, i-th label to be positioned all can be detected, and when the emissive power energy level of each reader will be
time, i-th label to be positioned all can not be detected.For arbitrary label to be positioned, record the neighbour's reference label within the scope of the minimum effective energy level of its coarseness, and generate the cognitive sequence of neighbour's reference label coarseness, the cognitive sequence of the neighbour's reference label coarseness as i-th label to be positioned is
p is the number of the cognitive sequence of neighbour's reference label coarseness.
According to power levels mapping function, map out the minimum effective energy level scope of fine granularity that the minimum effective energy level scope of coarseness of each label to be positioned is corresponding, the minimum effective energy level scope of the fine granularity as i-th label to be positioned is
union operation is carried out to whole elements of the minimum effective energy level scope of the fine granularity of whole label to be positioned, and by arranging from big to small, generates the fine granularity location radiation power sequence of reader.
Each reader in localizing environment is set to fine granularity Radiation work mode, according to fine granularity location radiation power sequence, arrive greatly little mode of successively decreasing step by step by reader emissive power to carry out fine granularity and accurately locate, generate the cognitive sequence of tag identity fine granularity to be positioned according to Monte Carlo mode
n is positioning label number.
For arbitrary label to be positioned, record the neighbour's reference label within the scope of the minimum effective energy level of its fine granularity, and generate the cognitive sequence of neighbour's reference label fine granularity, the cognitive sequence of the neighbour's reference label fine granularity as i-th label to be positioned is
q represents the cognitive sequence number of neighbour's reference label fine granularity.Loop cycle scan mechanism is set and performs fine granularity location, according to Monte Carlo mode, upgrade the cognitive sequence of neighbour's reference label fine granularity of each label to be positioned.
Adopt LANDMARC algorithm, obtain the positional information of label to be positioned.The cognitive coarseness sequence of tag identity more to be positioned and the cognitive fine granularity sequence of tag identity to be positioned, if the element number of fine granularity sequence is less than the element number of coarseness sequence, then show that there is certain label transfer to be positioned goes out localizing environment or enter into fine granularity power levels blind area, now return 3, carry out coarseness quick position.The cognitive sequence of neighbour's reference label fine granularity of more each label and the cognitive sequence of neighbour's reference label coarseness, if S when the two difference is greater than certain predetermined threshold value
r, then show that the path loss characteristics of indoor positioning environment changes, as artificial disturbance strengthen, Obstacle Position changes, humiture changes, now return step 3, reset power levels mapping function M{}.
In position fixing process, for the label newly-increased to be positioned in localizing environment, timing cycle scan mechanism is set, makes each reader perform coarseness radiation mode, upgrade the cognitive coarseness sequence of tag identity to be positioned.If judge, whether positioning result reaches set accuracy requirement and meets set constraint condition, then close reader, terminate this position fixing process.
Claims (2)
1., based on the frequency recognition positiming method that power intelligent controls, comprise the following steps:
Step 1: setting reader adopts coarseness radiation and fine granularity radiation two kinds of power emission modes;
Step 2: consider the path loss difference characteristic of different chamber's inner position environment, the layout density of reference label and the requirement of positioning precision and real-time, the power grade set of setting coarseness and fine granularity radiation;
Step 3: arrange multiple test point in indoor positioning environment, adopts nonlinear fitting mode to set up power levels mapping function;
Step 4: each reader arranged in localizing environment is coarseness Radiation work mode, the mode adopting emissive power energy level to successively decrease step by step from big to small carries out quick position, generates the cognitive sequence of tag identity coarseness to be positioned according to Monte Carlo method;
Step 5: for each label to be positioned, all sets up the minimum effective energy level scope of its coarseness;
Step 6: for each label to be positioned, records the neighbour's reference label within the scope of the minimum effective energy level of its coarseness, and generates the cognitive sequence of neighbour's reference label coarseness;
Step 7: according to power levels mapping function, map out the minimum effective energy level scope of fine granularity that the minimum effective energy level scope of coarseness of each label to be positioned is corresponding;
Step 8: union operation is carried out to whole elements of the minimum effective energy level scope of the fine granularity of whole label to be positioned, and by arranging from big to small, generate the fine granularity location radiation power sequence of reader;
Step 9: each reader in localizing environment is set to fine granularity Radiation work mode, according to fine granularity location radiation power sequence, arrive greatly little mode of successively decreasing step by step by reader emissive power to carry out fine granularity and accurately locate, generate the cognitive sequence of tag identity fine granularity to be positioned according to Monte Carlo method;
Step 10: for each label to be positioned, records the neighbour's reference label within the scope of the minimum effective energy level of its fine granularity, and generates the cognitive sequence of neighbour's reference label fine granularity;
Step 11: arrange loop cycle scan mechanism and perform fine granularity location, according to Monte Carlo mode, upgrades the cognitive sequence of neighbour's reference label fine granularity of each label to be positioned;
Step 12: adopt LANDMARC algorithm, obtain the positional information of label to be positioned;
Step 13: the cognitive coarseness sequence of tag identity more to be positioned and the cognitive fine granularity sequence of tag identity to be positioned, if the element number of fine granularity sequence is less than the element number of coarseness sequence, now return step 4, carry out coarseness quick position;
Step 14: the cognitive sequence of neighbour's reference label fine granularity of more each label and the cognitive sequence of neighbour's reference label coarseness, if S when the two difference is greater than certain predetermined threshold value
r, now return step 3, reset power levels mapping function M{ };
Step 15: for the label newly-increased to be positioned in localizing environment, arrange timing cycle scan mechanism, makes each reader perform coarseness radiation mode, upgrades the cognitive coarseness sequence of tag identity to be positioned;
Step 16: judge whether positioning result reaches set accuracy requirement, if meet set constraint condition, then close reader, terminate this position fixing process.
2., by a kind of frequency recognition positiming method controlled based on power intelligent described in right 1, it is characterized in that: the LANDMARC algorithm adopted in step 12, the position obtaining label to be positioned obtains by formula (1):
Wherein,
represent the estimated position of i-th label to be positioned,
represent the physical location of jth neighbour's reference label of i-th label to be positioned,
represent the bit-weight of jth neighbour's reference label of i-th label to be positioned, can be obtained by formula (2)
。
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| CN105929387A (en) * | 2016-05-26 | 2016-09-07 | 福建工程学院 | RFID (radio frequency identification) power transmitting level identification-based adaptive ranging method applied to tunnel |
| CN109727475A (en) * | 2017-10-27 | 2019-05-07 | 中移（杭州）信息技术有限公司 | Vehicle lookup method, device and communication equipment based on parking lot |
| US10395071B2 (en) | 2016-12-01 | 2019-08-27 | Avery Dennison Retail Information Services, Llc | Control of RFID reader emissions which may cause interference with systems using RFID tags |
| CN112055409A (en) * | 2020-08-04 | 2020-12-08 | 暨南大学 | RFID indoor positioning method based on power control |
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| CN105929387A (en) * | 2016-05-26 | 2016-09-07 | 福建工程学院 | RFID (radio frequency identification) power transmitting level identification-based adaptive ranging method applied to tunnel |
| CN105929387B (en) * | 2016-05-26 | 2018-12-07 | 福建工程学院 | Self application distance measuring method is identified based on RFID power emission shelves in tunnel |
| US10395071B2 (en) | 2016-12-01 | 2019-08-27 | Avery Dennison Retail Information Services, Llc | Control of RFID reader emissions which may cause interference with systems using RFID tags |
| CN109727475A (en) * | 2017-10-27 | 2019-05-07 | 中移（杭州）信息技术有限公司 | Vehicle lookup method, device and communication equipment based on parking lot |
| CN112055409A (en) * | 2020-08-04 | 2020-12-08 | 暨南大学 | RFID indoor positioning method based on power control |
| CN112055409B (en) * | 2020-08-04 | 2022-02-18 | 暨南大学 | RFID indoor positioning method based on power control |
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