CN106372553A - Pipeline matrix algorithm based on GJB radio frequency identification technology - Google Patents
Pipeline matrix algorithm based on GJB radio frequency identification technology Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
Abstract
The present invention discloses a pipeline matrix algorithm based on a GJB radio frequency identification technology. The method comprises the following steps: S1: constructing a dynamic feature matrix; S2, building a pipeline matrix, and performing matching summation point by point of the dynamic feature matrix and the pipeline matrix; and S3: decoding the matching summation result. The pipeline matrix algorithm based on a GJB radio frequency identification technology fully employs a parallel matching thinking to improve the checking code efficiency, and is an effective algorithm with high timeliness, small resource waste and high accuracy and dynamic regulation so as to reach the technology index being smaller than -75dB.
Description
Technical field
The invention belongs to RF identification communication technical field, it is based on gjb (national military standard) RF identification skill particularly to a kind of
The flowing water matrix algorithm of art.
Background technology
With the fast development of Internet of Things, the application of RF identification is more and more extensive, wherein to radio-frequency identification reader/writer
Identification sensitivity index and the requirement more and more higher reading distance.In military domain, the sensitivity index that industry it is generally desirable to is
It is less than -75db.But the product that current national military standard product can reach this index does not almost have.
Content of the invention
It is an object of the invention to overcoming prior art complicated due to wireless environment, checking code is likely to malfunction because of external interference
Deficiency, provide a kind of adopt flowing water matrix matching algorithm, take full advantage of the thinking of PARALLEL MATCHING, improve checking code efficiency,
Real-time is high, accuracy rate is high, can reach the flowing water matrix based on gjb REID of the technical specification being less than -75db
Algorithm.
The purpose of the present invention is achieved through the following technical solutions: the flowing water matrix based on gjb REID
Algorithm, comprises the following steps:
S1, structure behavioral characteristics matrix；
S2, set up flowing water matrix, and behavioral characteristics matrix and flowing water matrix are carried out pointwise and mate summation；
S3, the result to coupling summation are decoded.
Further, described step s1 concrete methods of realizing is: construction feature matrix model, the eigenmatrix of fm0 pattern
Two-dimentional shaping array for 10*16, be defined as { a0101, a0102 ..., a0116 }, a0201, a0202 ...,
A0216 } ..., { a1001, a1002, a1016 } }；
The content of above-mentioned matrix determines according to two aspects:
(1) 00+, 00-, 01+, 01-, 10+, 10-, 11+, 11-, v+, v- ten type is deposited according to fm0 pattern；
(2) amplitude of eigenmatrix is determined according to dynamic threshold；Dynamic threshold value determination method is: real-time sampling feature square
Battle array, 16 sampled points of length, according to the sequence of bubbling algorithm, maximum sequence the 1st, minima sequence the 16th；To sort the 3rd to
64 numbers are averaged, and are defined as profile maxima m1 of eigenmatrix；4 numbers of sequence the 11st to the 14th are averaged
Value, is defined as feature minima m0 of eigenmatrix；Remove sequence the 1st, the 2nd, the 7th, the 8th, the 9th, the 10th, the 15th, the 16th；?
To feature m1 represent the high level of decoding, feature m0 obtaining represents the low level of decoding；
According to above-mentioned determination principle, the whole parameters obtaining behavioral characteristics matrix are:
00+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
00-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
01+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
01-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
10+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
10-:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
11+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
11-:{ m0, m0, m0, m0, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
V+:{ m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0 }；
V-:{ m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0 }.
Further, described step s2 includes following sub-step:
S21, set up flowing water matrix model: flowing water matrix is the one-dimensional matrix of length 16, each clock cycle, one-dimensional matrix
Value shift renewal in real time, each cycle adds a new data, and first data of puncture table at matrix end；
In the n moment, flowing water matrix expression is: and bn, b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b (n+6),
B (n+7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15) }；
The expression formula of following clock cycle flowing water matrix is: { b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b
(n+6), b (n+7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15), b
(n+16)}；
Newly enter data b (n+16) and enter matrix, earliest data bn is moved out of matrix；
S22, carry out matching algorithm: in the n moment, the first row first row a0101 of behavioral characteristics matrix deducts current flowing water
Value b (n) of matrix, then takes the absolute value of difference, puts in accumulator acc0101, that is, acc0101 (n)=| a0101-b (n)
|；In the n+1 moment, the first row secondary series a0102 of behavioral characteristics matrix deducts value b (n+1) of current flowing water matrix, Ran Houqu
The absolute value of difference, puts in accumulator acc0101, that is, update acc0101 (n+1)=| a0101-b (n) |+| a0102-b (n-
1)|；Meanwhile, the first row first row a0101 of behavioral characteristics matrix is deducted value b (n+1) of current flowing water matrix, go difference
Absolute value, puts in accumulator acc0102, i.e. acc0102 (n+1)=| a0101-b (n+1) |；By that analogy, row formula is such as
Under:
Acc0101 (n)=| a0101-b (n-15) |+| a0102-b (n-14) |+...+| a0116-b (n) |；
Acc0102 (n)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |；
…
Acc0115 (n)=| a0101-b (n-1) |+| a0102-b (n) |；
Acc0116 (n)=| a0101-b (n) |；
In the n moment, acc0101 has added up and has counted full 16 numbers, derives and deposits as r0101；
In the n+1 moment, expression formula is as follows:
Acc0101 (n+1)=| a0101-b (n+1) |；
Acc0102 (n+1)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |+| a0116-
b(n+1)|；
…
Acc0115 (n+1)=| a0101-b (n-1) |+| a0102-b (n) |+| a0103-b (n+1) |；
Acc0116 (n+1)=| a0101-b (n) |+| a0102-b (n+1) |；
Now, acc0102 has added up and has counted full 16 numbers, derives and deposits as r0102；
By that analogy, produce r0101～r0116；
Eigenmatrix second row carries out above-mentioned identical operation and draws r0201～r0216；Eigenmatrix the third line computing draws
R0301～r0316；By that analogy ..., eigenmatrix the tenth row operation draws r1001～r1016.
While obtaining rxx01～rxx16, each 16 number deposited is ranked up, suitable according to from small to large
Sequence is followed successively by r ' xx01～r ' xx16, and less value shows higher with eigenmatrix matching degree；S23, matrix is rearranged, its
Middle r ' 0101 represents the matching value optimal with eigenmatrix the first row, and r ' 0201 represents and eigenmatrix second optimal the mating of row
Value ..., r ' 1001 represents the matching value optimal with eigenmatrix the tenth row；By r ' 0101, r ' 0201 ..., r ' 1001 carries out two
Minor sort, order from small to large is followed successively by min01, min ' 02 ..., min ' 16.
Further, described step s3 includes following sub-step:
S31, searching coding head, find coding head by matching result, the timing when r ' 0901 occurs in min01 position is opened
Begin, judge that subsequent r ' 1001 occurs in the time interval of min01 position, when this time interval is between ± tc*3*%25%, its
In, tc is the fiducial time of forward link, then judge current time as volume terminal locations；
S32, carry out checking code operation: after finding coding head, start checking code state machine；
(1) state description of checking code state machine:
S000, checking code pattern 00, polarity is by high level；
S001, checking code pattern 00, polarity is by low level；
S010, checking code pattern 01, polarity is by high level；
S011, checking code pattern 01, polarity is by low level；
S100, checking code pattern 10, polarity is by high level；
S101, checking code pattern 10, polarity is by low level；
S110, checking code pattern 11, polarity is by high level；
S111, checking code pattern 11, polarity is by low level；
(2) the state transition condition stub of checking code state machine:
1. inlet condition idle is to the explanation that redirects of each state: starts timing, when timing is between ± tc*2*25%, occurs
The corresponding abscissa positions of r ' xxxx in min01 position:
If 01, then jump to s000；
If 02, then jump to s001；
If 03, then jump to s010；
If 04, then jump to s011；
If 05, then jump to s100；
If 06, then jump to s101；
If 07, then jump to s110；
If 08, then jump to s111；
2. each state transition explanation: when entering s000 state, then start timing, when timing is between ± tc*2*25%, according to
The corresponding abscissa of r ' xxxx occurring in min01 position carries out redirecting judgement:
Redirect condition 1: if corresponding abscissa is 01, jump back to current state from s000, simultaneously Updating time
Reclocking；
Redirect condition 2: if corresponding abscissa is 03, jump to s010 from s000, Updating time is again simultaneously
Timing；
Other abscissas occur do not redirected；
If abscissa not only occurred 01 but also occur 03, compare the value of r ' xxxx, using less value corresponding abscissa as
Criterion；
Timer reclocking, when timing is between ± tc*2*25%, the r ' xxxx according to occurring in min01 position corresponds to
Abscissa carry out redirecting judgement:
Redirect condition 3: if corresponding abscissa is 02, jump back to current state from s001, simultaneously Updating time
Reclocking；
Redirect condition 4: if corresponding abscissa is 04, jump to s011 from s001, Updating time is again simultaneously
Timing；
If abscissa not only occurred 02 but also occur 04, compare the value of r ' xxxx, using less value corresponding abscissa as
Criterion；
By that analogy, repeat above-mentioned reclocking and judge process, redirected condition as follows:
Redirect condition 5: if corresponding abscissa is 05, jump to s100 from s010, Updating time is again simultaneously
Timing；
Redirect condition 6: if corresponding abscissa is 07, jump to s110 from s010, Updating time is again simultaneously
Timing；
Redirect condition 7: if corresponding abscissa is 06, jump to s101 from s011, Updating time is again simultaneously
Timing；
Redirect condition 8: if corresponding abscissa is 08, jump to s111 from s011, Updating time is again simultaneously
Timing；
Redirect condition 9: if corresponding abscissa is 04, jumps and go to s011 from s100, Updating time is counted again simultaneously
When；
Redirect condition 10: if corresponding abscissa is 02, jump to s001 from s100, Updating time is again simultaneously
Timing；
Redirect condition 11: if corresponding abscissa is 03, jump to s010 from s101, Updating time is again simultaneously
Timing；
Redirect condition 12: if corresponding abscissa is 01, jump to s000 from s101, Updating time is again simultaneously
Timing；
Redirect condition 13: if corresponding abscissa is 06, jump to s101 from s110, Updating time is again simultaneously
Timing；
Redirect condition 14: if corresponding abscissa is 08, jump to s111 from s110, Updating time is again simultaneously
Timing；
Redirect condition 15: if corresponding abscissa is 07, jump to s110 from s111, Updating time is again simultaneously
Timing；
Redirect condition 16: if corresponding abscissa is 05, jump to s100 from s111, Updating time is again simultaneously
Timing；
3. state machine output: when state s000, s001, s010, s011 jump out, checking code output data 0；From state
When s100, s101, s110, s111 jump out, checking code output data 1, complete checking code.
The invention has the beneficial effects as follows:
1st, the flowing water matrix matching algorithm of the present invention, takes full advantage of the thinking of PARALLEL MATCHING, improves checking code efficiency；?
Be that a kind of real-time is high, expend that resource is few, accuracy rate is high, being dynamically adapted effective is said on the decoding technique aspect of RF identification
Algorithm, can reach the technical specification less than -75db；
2nd, by the way of based on comparing, select more to meet and send the code element model being intended to, symbol dependency makes in front and back
Obtain the present invention and there is fault-tolerance, thus checking code ability is higher.
Brief description
Fig. 1 is the checking code state machine state figure of the present invention.
Specific embodiment
Further illustrate technical scheme below in conjunction with the accompanying drawings.
Flowing water matrix algorithm based on gjb REID is it is characterised in that comprise the following steps:
S1, structure behavioral characteristics matrix；Concrete methods of realizing is: construction feature matrix model, the eigenmatrix of fm0 pattern
Two-dimentional shaping array for 10*16, be defined as { a0101, a0102 ..., a0116 }, a0201, a0202 ...,
A0216 } ..., { a1001, a1002, a1016 } }；
The content of above-mentioned matrix determines according to two aspects:
(1) 00+, 00-, 01+, 01-, 10+, 10-, 11+, 11-, v+, v- ten type is deposited according to fm0 pattern；
(2) amplitude of eigenmatrix is determined according to dynamic threshold；Dynamic threshold value determination method is: real-time sampling feature square
Battle array, 16 sampled points of length, according to the sequence of bubbling algorithm, maximum sequence the 1st, minima sequence the 16th；To sort the 3rd to
64 numbers are averaged, and are defined as profile maxima m1 of eigenmatrix；4 numbers of sequence the 11st to the 14th are averaged
Value, is defined as feature minima m0 of eigenmatrix；Remove sequence the 1st, the 2nd, the 7th, the 8th, the 9th, the 10th, the 15th, the 16th；?
To feature m1 represent the high level of decoding, feature m0 obtaining represents the low level of decoding；
According to above-mentioned determination principle, the whole parameters obtaining behavioral characteristics matrix are:
00+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
00-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
01+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
01-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
10+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
10-:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
11+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
11-:{ m0, m0, m0, m0, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
V+:{ m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0 }；
V-:{ m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0 }.
S2, set up flowing water matrix, and behavioral characteristics matrix and flowing water matrix are carried out pointwise and mate summation；Including following son
Step:
S21, set up flowing water matrix model: flowing water matrix is the one-dimensional matrix of length 16, each clock cycle, one-dimensional matrix
Value shift renewal in real time, each cycle adds a new data, and first data of puncture table at matrix end；Stream
Water matrix model is as shown in Table 1.
Table one
| clkn-15 | clkn-14 | clkn-13 | clkn-12 | clkn-11 | clkn-10 | clkn-9 | clkn-8 | clkn-7 |
| bn-15 | bn-14 | bn-13 | bn-12 | bn-11 | bn-10 | bn-9 | bn-8 | bn-7 |
| |a1-bn-15 | | |a1-bn-14 | | |a1-bn-13 | | |a1-bn-12 | | |a1-bn-11 | | |a1-bn-10 | | |a1-bn-9 | | |a1-bn-8 | | |a1-bn-7| |
| |a2-bn-14 | | |a2-bn-13 | | |a2-bn-12 | | |a2-bn-11 | | |a2-bn-10 | | |a2-bn-9 | | |a2-bn-8 | | |a2-bn-7| | |
| |a3-bn-13 | | |a3-bn-12 | | |a3-bn-11 | | |a3-bn-10 | | |a3-bn-9 | | |a3-bn-8 | | |a3-bn-7| | ||
| |a4-bn-12 | | |a4-bn-11 | | |a4-bn-10 | | |a4-bn-9 | | |a4-bn-8 | | |a4-bn-7| | |||
| |a5-bn-11 | | |a5-bn-10 | | |a5-bn-9 | | |a5-bn-8 | | |a5-bn-7| | ||||
| |a6-bn-10 | | |a6-bn-9 | | |a6-bn-8 | | |a6-bn-7| | |||||
| |a7-bn-9 | | |a7-bn-8 | | |a7-bn-7| | ||||||
| |a8-bn-8 | | |a8-bn-7| | |||||||
| |a9-bn-7| | ||||||||
Continued
In the n moment, flowing water matrix expression is: and bn, b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b (n+6),
B (n+7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15) }；
The expression formula of following clock cycle flowing water matrix is: { b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b
(n+6), b (n+7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15), b
(n+16)}；
Newly enter data b (n+16) and enter matrix, earliest data bn is moved out of matrix；
S22, carry out matching algorithm: in the n moment, the first row first row a0101 of behavioral characteristics matrix deducts current flowing water
Value b (n) of matrix, then takes the absolute value of difference, puts in accumulator acc0101, that is, acc0101 (n)=| a0101-b (n)
|；In the n+1 moment, the first row secondary series a0102 of behavioral characteristics matrix deducts value b (n+1) of current flowing water matrix, Ran Houqu
The absolute value of difference, puts in accumulator acc0101, that is, update acc0101 (n+1)=| a0101-b (n) |+| a0102-b (n-
1)|；Meanwhile, the first row first row a0101 of behavioral characteristics matrix is deducted value b (n+1) of current flowing water matrix, go difference
Absolute value, puts in accumulator acc0102, i.e. acc0102 (n+1)=| a0101-b (n+1) |；By that analogy, row formula is such as
Under:
Acc0101 (n)=| a0101-b (n-15) |+| a0102-b (n-14) |+...+| a0116-b (n) |；
Acc0102 (n)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |；
…
Acc0115 (n)=| a0101-b (n-1) |+| a0102-b (n) |；
Acc0116 (n)=| a0101-b (n) |；
In the n moment, acc0101 has added up and has counted full 16 numbers, derives and deposits as r0101；
In the n+1 moment, expression formula is as follows:
Acc0101 (n+1)=| a0101-b (n+1) |；
Acc0102 (n+1)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |+| a0116-
b(n+1)|；
…
Acc0115 (n+1)=| a0101-b (n-1) |+| a0102-b (n) |+| a0103-b (n+1) |；
Acc0116 (n+1)=| a0101-b (n) |+| a0102-b (n+1) |；
Now, acc0102 has added up and has counted full 16 numbers, derives and deposits as r0102；
By that analogy, produce r0101～r0116；
Eigenmatrix second row carries out above-mentioned identical operation and draws r0201～r0216；Eigenmatrix the third line computing draws
R0301～r0316；By that analogy ..., eigenmatrix the tenth row operation draws r1001～r1016.
Because the present invention is to be realized based on fpga, while therefore obtaining rxx01～rxx16,16 that each is deposited
Number is ranked up, and is followed successively by r ' xx01～r ' xx16 according to order from small to large, and less value shows and eigenmatrix
Degree of joining is higher；, by the matching degree real-time quantization of pattern, matching degree is higher for the present invention, and r ' xxxx is lower for matching result, minimum
Join the horizontal stroke of value, vertical coordinate shows optimal coupling pattern and opportunity；
S23, matrix is rearranged, wherein r ' 0101 represents the matching value optimal with eigenmatrix the first row, r ' 0201
Represent the matching value ... optimal with eigenmatrix second row, r ' 1001 represents the matching value optimal with eigenmatrix the tenth row；Will
R ' 0101, r ' 0201 ..., r ' 1001 carries out two minor sorts, and order from small to large is followed successively by min01, min ' 02 ..., min '
16.
S3, the result to coupling summation are decoded, including following sub-step:
S31, searching coding head, find coding head by matching result, the timing when r ' 0901 occurs in min01 position is opened
Begin, judge that subsequent r ' 1001 occurs in the time interval of min01 position, when this time interval is between ± tc*3*%25%, its
In, tc is the fiducial time of forward link, then judge current time as volume terminal locations；
S32, carry out checking code operation: after finding coding head, start checking code state machine；
(1) state description of checking code state machine:
S000, checking code pattern 00, polarity is by high level；
S001, checking code pattern 00, polarity is by low level；
S010, checking code pattern 01, polarity is by high level；
S011, checking code pattern 01, polarity is by low level；
S100, checking code pattern 10, polarity is by high level；
S101, checking code pattern 10, polarity is by low level；
S110, checking code pattern 11, polarity is by high level；
S111, checking code pattern 11, polarity is by low level；
(2) the state transition condition stub of checking code state machine:
The condition number that redirects of the state machine of the present invention is shown in Fig. 1.For ease of the bar redirecting between the description each state of state machine
Part, state transition path is numbered in FIG.
1. inlet condition idle is to the explanation that redirects of each state: starts timing, when timing is between ± tc*2*25%, occurs
The corresponding abscissa positions of r ' xxxx in min01 position:
If 01, then jump to s000；
If 02, then jump to s001；
If 03, then jump to s010；
If 04, then jump to s011；
If 05, then jump to s100；
If 06, then jump to s101；
If 07, then jump to s110；
If 08, then jump to s111；
2. each state transition explanation: when entering s000 state, then start timing, when timing is between ± tc*2*25%, according to
The corresponding abscissa of r ' xxxx occurring in min01 position carries out redirecting judgement:
Redirect condition 1: if corresponding abscissa is 01, jump back to current state from s000, simultaneously Updating time
Reclocking；
Redirect condition 2: if corresponding abscissa is 03, jump to s010 from s000, Updating time is again simultaneously
Timing；
Other abscissas occur do not redirected；
If abscissa not only occurred 01 but also occur 03, compare the value of r ' xxxx, using less value corresponding abscissa as
Criterion；
Timer reclocking, when timing is between ± tc*2*25%, the r ' xxxx according to occurring in min01 position corresponds to
Abscissa carry out redirecting judgement:
Redirect condition 3: if corresponding abscissa is 02, jump back to current state from s001, simultaneously Updating time
Reclocking；
Redirect condition 4: if corresponding abscissa is 04, jump to s011 from s001, Updating time is again simultaneously
Timing；
If abscissa not only occurred 02 but also occur 04, compare the value of r ' xxxx, using less value corresponding abscissa as
Criterion；
By that analogy, repeat above-mentioned reclocking and judge process, redirected condition as follows:
Redirect condition 5: if corresponding abscissa is 05, jump to s100 from s010, Updating time is again simultaneously
Timing；
Redirect condition 6: if corresponding abscissa is 07, jump to s110 from s010, Updating time is again simultaneously
Timing；
Redirect condition 7: if corresponding abscissa is 06, jump to s101 from s011, Updating time is again simultaneously
Timing；
Redirect condition 8: if corresponding abscissa is 08, jump to s111 from s011, Updating time is again simultaneously
Timing；
Redirect condition 9: if corresponding abscissa is 04, jumps and go to s011 from s100, Updating time is counted again simultaneously
When；
Redirect condition 10: if corresponding abscissa is 02, jump to s001 from s100, Updating time is again simultaneously
Timing；
Redirect condition 11: if corresponding abscissa is 03, jump to s010 from s101, Updating time is again simultaneously
Timing；
Redirect condition 12: if corresponding abscissa is 01, jump to s000 from s101, Updating time is again simultaneously
Timing；
Redirect condition 13: if corresponding abscissa is 06, jump to s101 from s110, Updating time is again simultaneously
Timing；
Redirect condition 14: if corresponding abscissa is 08, jump to s111 from s110, Updating time is again simultaneously
Timing；
Redirect condition 15: if corresponding abscissa is 07, jump to s110 from s111, Updating time is again simultaneously
Timing；
Redirect condition 16: if corresponding abscissa is 05, jump to s100 from s111, Updating time is again simultaneously
Timing；
3. state machine output: when state s000, s001, s010, s011 jump out, checking code output data 0；From state
When s100, s101, s110, s111 jump out, checking code output data 1, complete checking code.
The present invention only need to change eigenmatrix parameter, you can for checking code Miller pattern: the characteristic model that the present invention builds
It is based on fm0, invention thinking is equally applicable to Miller pattern.Only eigenmatrix parameter need to be replaced with the parameter of Miller.
Because invention thinking is identical, herein not in citing, but every checking code according to the realization of above-mentioned algorithm belongs to the present invention
Scope.
In sum, under the fm0 and Miller code model of RF identification, the embodiment of the present invention compares current other system
There is simpler and more direct, efficient advantage.
Those of ordinary skill in the art will be appreciated that, embodiment described here is to aid in reader and understands this
Bright principle is it should be understood that protection scope of the present invention is not limited to such special statement and embodiment.This area
Those of ordinary skill can make various other each without departing from present invention essence according to these technology disclosed by the invention enlightenment
Plant concrete deformation and combine, these deform and combine still within the scope of the present invention.
Claims (4)
1. the flowing water matrix algorithm based on gjb REID is it is characterised in that comprise the following steps:
S1, structure behavioral characteristics matrix；
S2, set up flowing water matrix, and behavioral characteristics matrix and flowing water matrix are carried out pointwise and mate summation；
S3, the result to coupling summation are decoded.
2. the flowing water matrix algorithm based on gjb REID according to claim 1 is it is characterised in that described step
Rapid s1 concrete methods of realizing is: construction feature matrix model, and the eigenmatrix of fm0 pattern is the two-dimentional shaping array of 10*16, fixed
Justice is { { a0101, a0102 ..., a0116 }, { a0201, a0202 ..., a0216 } ..., { a1001, a1002, a1016 } }；
The content of above-mentioned matrix determines according to two aspects:
(1) 00+, 00-, 01+, 01-, 10+, 10-, 11+, 11-, v+, v- ten type is deposited according to fm0 pattern；
(2) amplitude of eigenmatrix is determined according to dynamic threshold；Dynamic threshold value determination method is: real-time sampling eigenmatrix,
16 sampled points of length, according to the sequence of bubbling algorithm, maximum sequence the 1st, minima sequence the 16th；By sequence the 3rd to the 6th
4 numbers are averaged, and are defined as profile maxima m1 of eigenmatrix；4 numbers of sequence the 11st to the 14th are averaged, really
It is set to feature minima m0 of eigenmatrix；Remove sequence the 1st, the 2nd, the 7th, the 8th, the 9th, the 10th, the 15th, the 16th；Obtain
Feature m1 represents the high level of decoding, and feature m0 obtaining represents the low level of decoding；
According to above-mentioned determination principle, the whole parameters obtaining behavioral characteristics matrix are:
00+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
00-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
01+:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
01-:{ m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
10+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1 }；
10-:{ m1, m1, m1, m1, m0, m0, m0, m0, m1, m1, m1, m1, m0, m0, m0, m0 }；
11+:{ m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0 }；
11-:{ m0, m0, m0, m0, m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1 }；
V+:{ m0, m0, m0, m0, m1, m1, m1, m1, m1, m1, m1, m1, m0, m0, m0, m0 }；
V-:{ m1, m1, m1, m1, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0, m0 }.
3. the flowing water matrix algorithm based on gjb REID according to claim 2 is it is characterised in that described step
Rapid s2 includes following sub-step:
S21, set up flowing water matrix model: flowing water matrix is the one-dimensional matrix of length 16, each clock cycle, the value of one-dimensional matrix
Displacement updates in real time, and each cycle adds a new data at matrix end, and first data of puncture table；
In the n moment, flowing water matrix expression is: { bn, b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b (n+6), b (n+
7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15) }；
The expression formula of following clock cycle flowing water matrix is: { b (n+1), b (n+2), b (n+3), b (n+4), b (n+5), b (n+
6), b (n+7), b (n+8), b (n+9), b (n+10), b (n+11), b (n+12), b (n+13), b (n+14), b (n+15), b (n+
16)}；
Newly enter data b (n+16) and enter matrix, earliest data bn is moved out of matrix；
S22, carry out matching algorithm: in the n moment, the first row first row a0101 of behavioral characteristics matrix deducts current flowing water matrix
Value b (n), then take the absolute value of difference, put in accumulator acc0101, be i.e. acc0101 (n)=| a0101-b (n) |；n+
In 1 moment, the first row secondary series a0102 of behavioral characteristics matrix deducts value b (n+1) of current flowing water matrix, then takes difference
Absolute value, put in accumulator acc0101, that is, update acc0101 (n+1)=| a0101-b (n) |+| a0102-b (n-1) |；
Meanwhile, the first row first row a0101 of behavioral characteristics matrix is deducted value b (n+1) of current flowing water matrix, remove the absolute of difference
Value, puts in accumulator acc0102, i.e. acc0102 (n+1)=| a0101-b (n+1) |；By that analogy, row formula is as follows:
Acc0101 (n)=| a0101-b (n-15) |+| a0102-b (n-14) |+...+| a0116-b (n) |；
Acc0102 (n)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |；
…
Acc0115 (n)=| a0101-b (n-1) |+| a0102-b (n) |；
Acc0116 (n)=| a0101-b (n) |；
In the n moment, acc0101 has added up and has counted full 16 numbers, derives and deposits as r0101；
In the n+1 moment, expression formula is as follows:
Acc0101 (n+1)=| a0101-b (n+1) |；
Acc0102 (n+1)=| a0101-b (n-14) |+| a0102-b (n-12) |+...+| a0115-b (n) |+| a0116-b (n+
1)|；
…
Acc0115 (n+1)=| a0101-b (n-1) |+| a0102-b (n) |+| a0103-b (n+1) |；
Acc0116 (n+1)=| a0101-b (n) |+| a0102-b (n+1) |；
Now, acc0102 has added up and has counted full 16 numbers, derives and deposits as r0102；
By that analogy, produce r0101～r0116；
Eigenmatrix second row carries out above-mentioned identical operation and draws r0201～r0216；Eigenmatrix the third line computing draws
R0301～r0316；By that analogy ..., eigenmatrix the tenth row operation draws r1001～r1016.
Obtain rxx01～rxx16 while, each 16 number deposited is ranked up, according to order from small to large according to
Secondary for r ' xx01～r ' xx16, less value shows higher with eigenmatrix matching degree；S23, matrix is rearranged, wherein r '
0101 represents the matching value optimal with eigenmatrix the first row, and r ' 0201 represents and eigenmatrix second optimal the mating of row
Value ..., r ' 1001 represents the matching value optimal with eigenmatrix the tenth row；By r ' 0101, r ' 0201 ..., r ' 1001 carries out two
Minor sort, order from small to large is followed successively by min01, min ' 02 ..., min ' 16.
4. the flowing water matrix algorithm based on gjb REID according to claim 3 is it is characterised in that described step
Rapid s3 includes following sub-step:
S31, searching coding head, find coding head by matching result, the timing when r ' 0901 occurs in min01 position starts,
Judge that subsequent r ' 1001 occurs in the time interval of min01 position, when this time interval is between ± tc*3*%25%, wherein,
Tc is the fiducial time of forward link, then judge current time as volume terminal locations；
S32, carry out checking code operation: after finding coding head, start checking code state machine；
(1) state description of checking code state machine:
S000, checking code pattern 00, polarity is by high level；
S001, checking code pattern 00, polarity is by low level；
S010, checking code pattern 01, polarity is by high level；
S011, checking code pattern 01, polarity is by low level；
S100, checking code pattern 10, polarity is by high level；
S101, checking code pattern 10, polarity is by low level；
S110, checking code pattern 11, polarity is by high level；
S111, checking code pattern 11, polarity is by low level；
(2) the state transition condition stub of checking code state machine:
1. inlet condition idle is to the explanation that redirects of each state: starts timing, when timing is between ± tc*2*25%, occurs in
The corresponding abscissa positions of r ' xxxx of min01 position:
If 01, then jump to s000；
If 02, then jump to s001；
If 03, then jump to s010；
If 04, then jump to s011；
If 05, then jump to s100；
If 06, then jump to s101；
If 07, then jump to s110；
If 08, then jump to s111；
2. each state transition explanation: when entering s000 state, then start timing, when timing is between ± tc*2*25%, according to appearance
The corresponding abscissa of r ' xxxx in min01 position carries out redirecting judgement:
Redirect condition 1: if corresponding abscissa is 01, jump back to current state from s000, Updating time is again simultaneously
Timing；
Redirect condition 2: if corresponding abscissa is 03, jump to s010 from s000, simultaneously Updating time reclocking；
Other abscissas occur do not redirected；
If abscissa had not only occurred 01 but also occur 03, compare the value of r ' xxxx, using the corresponding abscissa of less value as judgement
Standard；
Timer reclocking, when timing is between ± tc*2*25%, according to the corresponding horizontal stroke of r ' xxxx occurring in min01 position
Coordinate carries out redirecting judgement:
Redirect condition 3: if corresponding abscissa is 02, jump back to current state from s001, Updating time is again simultaneously
Timing；
Redirect condition 4: if corresponding abscissa is 04, jump to s011 from s001, simultaneously Updating time reclocking；
If abscissa had not only occurred 02 but also occur 04, compare the value of r ' xxxx, using the corresponding abscissa of less value as judgement
Standard；
By that analogy, repeat above-mentioned reclocking and judge process, redirected condition as follows:
Redirect condition 5: if corresponding abscissa is 05, jump to s100 from s010, simultaneously Updating time reclocking；
Redirect condition 6: if corresponding abscissa is 07, jump to s110 from s010, simultaneously Updating time reclocking；
Redirect condition 7: if corresponding abscissa is 06, jump to s101 from s011, simultaneously Updating time reclocking；
Redirect condition 8: if corresponding abscissa is 08, jump to s111 from s011, simultaneously Updating time reclocking；
Redirect condition 9: if corresponding abscissa is 04, jumps and go to s011 from s100, Updating time reclocking simultaneously；
Redirect condition 10: if corresponding abscissa is 02, jump to s001 from s100, Updating time is counted again simultaneously
When；
Redirect condition 11: if corresponding abscissa is 03, jump to s010 from s101, Updating time is counted again simultaneously
When；
Redirect condition 12: if corresponding abscissa is 01, jump to s000 from s101, Updating time is counted again simultaneously
When；
Redirect condition 13: if corresponding abscissa is 06, jump to s101 from s110, Updating time is counted again simultaneously
When；
Redirect condition 14: if corresponding abscissa is 08, jump to s111 from s110, Updating time is counted again simultaneously
When；
Redirect condition 15: if corresponding abscissa is 07, jump to s110 from s111, Updating time is counted again simultaneously
When；
Redirect condition 16: if corresponding abscissa is 05, jump to s100 from s111, Updating time is counted again simultaneously
When；
3. state machine output: when state s000, s001, s010, s011 jump out, checking code output data 0；From state s100,
When s101, s110, s111 jump out, checking code output data 1, complete checking code.
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| CN102522996A (en) * | 2011-12-08 | 2012-06-27 | 北京握奇数据系统有限公司 | Decoding method and decoding device of FM0 coded data |
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