CN104537874A - Method for looking for car in indoor parking area based on triangular area location - Google Patents

Abstract

The invention provides a method for looking for a car in an indoor parking area based on triangular area location. A location system with an LANDMARC structure is structured. A scan-round is carried out by all readers. When a label to be positioned is detected by three readers, binary string matrixes and conditions of reference label reading are written down and then a nearest neighbor is chosen, the position coordinates of the label to be positioned is calculated by utilizing the coordinates of the nearest neighbor, and the positions of all the labels to be positioned are double calculated. The method for looking for the car in the indoor parking area based on triangular area location enables the hardware cost of structuring the location system to be reduced. The location system adapts to indoor environmental dynamic uncertainty caused by wall or object sheltering, reader efficacy losing and other changes. When the number of readers is large, calculated amount is reduced effectively and the precision of location is improved.

Description

Car method is sought in parking garage based on location, Delta Region

Technical field

The invention belongs to intelligent transportation system electronic technology field, relate to the real-time intelligent area positioning method based on RFID.

Background technology

At present, kind more than 20 is had all to relate to the real-time location of vehicle in 33 kinds of customer services of intelligent transportation system (ITS, Intelligent Transport System) framework.Therefore, the focus that vehicle real time positioning technology accurately and efficiently becomes recent intelligent transportation field is studied.The embody rule that the problem of seeking car difficulty when car owner leaves the theatre just belongs to this research is solved in intelligent parking management system.

What realize parking garage seeks car fast, and its core is the location algorithm of efficiently and accurately.Current, common indoor positioning mainly utilizes infrared, the technology such as WLAN (wireless local area network), ultrasound wave, ultra broadband and radio-frequency (RF) identification, realizes according to different location algorithms.

REID (RFID) is the one starting the automatic identification technology risen the nineties in 20th century, namely utilize wireless radio frequency mode to carry out noncontact bidirectional data communication, information input can be completed without the need to manual intervention and process and realize being identified target.RFID technique energy consumption is low, all can apply under various rugged surroundings, can be widely used in the needs such as production, logistics, medical treatment, traffic, transport, tracking, false proof, equipment and asset management to collect and the field of process data, being known as by industry is one of the most promising application technology in this century.

Current, like a raging fire to the localization method research based on RFID, and related algorithm is also varied, mainly contains TOA algorithm, TDOA algorithm, RSSI algorithm and AOA algorithm etc.In four kinds of algorithms most in use described above, TOA and TDOA positioning requirements reader and label are strictly consistent in time, and use AOA algorithm to need to install expensive receiving antenna array to reader, these three kinds of method hardware costs are all higher.

LANDMARC system based on RSSI algorithm carries out auxiliary positioning by reference to label, " nearest-neighbors " is selected with the signal intensity difference between label to be positioned according to reference label, then the positional information of label to be positioned is obtained by weighted calculation, the method improves the positioning precision of system when not increasing the hardware device costs such as reader, and because reference label and label to be positioned are under identical environment in LANDMARC positioning system, namely the impact of dynamic change on both of environment is equivalent, therefore, the dynamic change that the method can well conform, be at present research extensively and the indoor positioning algorithms comparatively given prominence to of odds ratio.

But there are two large deficiencies when solving " nearest-neighbors " in LANDMARC location algorithm: (1) all reference label participate in calculating as candidate's label of " nearest-neighbors ", bring the significantly increase of calculated amount; (2) by existing route loss formula cause " when label from reader distance more away from time, loss of signal is faster, and error is larger ".

Summary of the invention

In order to overcome the deficiencies in the prior art, the invention provides location, a kind of parking garage based on nearest-neighbors and seeking car method, locating in real time to realize vehicle in intelligent parking lot, helping car owner to seek car fast and leave the theatre, effectively improve parking lot utilization ratio.

The technical solution adopted for the present invention to solve the technical problems comprises the following steps:

(1) build the positioning system of a LANDMARC framework, have reader M that is evenly arranged in system, M >=3, the reference label that position coordinates is known is N number of, and reader energy level is divided into 1-8 level;

(2) define each label to be positioned and reference label is 8 binary strings, initialization each be 0;

(3) every 30s, all readers carry out a scan round from 1 to 8 energy levels simultaneously; If certain label to be positioned is read, just by the r position 1 of corresponding binary string when power grade r by reader j; Write down the binary string matrix of now N number of reference label respectively $R=\left[\begin{array}{cccc}{R}_{11}& R_{12}& ...& R_{1M}\\ R_{21}& R_{22}& ...& R_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ R_{N1}& R_{N2}& ...& R_{\mathrm{NM}}\end{array}\right]$ The binary string matrix corresponding with L label to be positioned $T=\left[\begin{array}{cccc}{T}_{11}& T_{12}& ...& T_{1M}\\ T_{21}& T_{22}& ...& T_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ T_{N1}& T_{N2}& ...& T_{\mathrm{NM}}\end{array}\right],$ Wherein, R _ijrepresent the binary string that i-th reference label is corresponding with a jth reader, T _ljrepresent the binary string that l label to be positioned is corresponding with a jth reader, i ∈ (1, N), l ∈ (1, L), j ∈ (1, M);

(4) for certain concrete label Tag_p to be positioned, find out successively from matrix T containing 1 three maximum readers, be designated as Reader_a, Reader_b and Reader_c, and binary string corresponding for these three readers is combined into new matrix T _p=[T _pat _pbt _pc];

(5) from matrix R, choose reference label corresponding to reader Reader_a, Reader_b and Reader_c and binary string, remove full zero row, form new matrix $R^{\′}=\left[\begin{array}{ccc}{R}_{1a}^{\′}& R_{1b}^{\′}& R_{1c}^{\′}\\ R_{2a}^{\′}& R_{2b}^{\′}& R_{2c}^{\′}\\ .& .& .\\ .& .& .\\ .& .& .\\ R_{\mathrm{xa}}^{\′}& R_{\mathrm{xb}}^{\′}& R_{\mathrm{xc}}^{\′}\end{array}\right],$ X indicates x reference label;

(6) by matrix T _pcarry out AND operation bit-by-bit with the corresponding element in R ', its matrix of consequence is designated as

(7) by matrix T R ' often row in complete zero binary string set to 0, non-full zero scale-of-two tandem arrangement 1, forms new matrix T R _p;

(8) compute matrix TR _pthe often number of row 1, gets the reference label of the capable representative of front k as nearest-neighbors from big to small according to the number of every row 1; K>=4;

(9) coordinate (x of nearest-neighbors is utilized _i, y _i) calculate the position coordinates of label to be positioned wherein, w _ibe in the i-th row 1 number account for selected k capable in 1 the number percent of number;

(10) repeat step (4) ~ (9), calculate the position of all labels undetermined.

The invention has the beneficial effects as follows:

(1) overcome in traditional algorithm by reader reading tag signal strength values, calculate the deficiency of the position coordinates of label to be positioned, have employed more how cheap reference label and instead of expensive reader, make to build the hardware costs of positioning system to greatly reduce, can also adapt to preferably in indoor environment due to body of wall or object block, reader inefficacy etc. changes the dynamic uncertainty brought;

(2) algorithm after improving considers that " reference value of the reference label that range reader is far away is less, if this kind of reference label to be taken into account the positioning precision that finally can affect whole system " the fact, based on " no matter what position label to be positioned is in, capital is in the delta-shaped region of three reader formations around it, and ' nearest-neighbors ' reference label of this label to be positioned choose the Delta Region scope that also must come from these three readers and be formed ", when positioning, nearest-neighbors label is chosen by within the scope of nearest apart from label to be positioned three reader read-writes, such processing mode is when read write line is a fairly large number of, effectively can reduce calculated amount, and owing to eliminating remote " bad " reference label to the impact of positioning precision, the precision of location can also be improved to a certain extent,

(3) the inventive method is by all readers from the single pass of 1 to 8 energy levels, just can complete the analytical calculation of the label multiple undetermined in region simultaneously, obtain its position.

The method is well positioned to meet the requirement of parking lot indoor locating system.The method is applied in the middle of modern Intelligent parking lot management system, the function of parking management system can be improved, realize seeking car fast when car owner leaves, improve service quality and make it have more hommization, parking stall utilization factor can also be improved to a certain extent.

Accompanying drawing explanation

Fig. 1 is the flowchart of the inventive method;

Fig. 2 is label and reader distribution schematic diagram;

Fig. 3 is the deviation accumulation distribution plan of two kinds of algorithms.

Embodiment

Below in conjunction with drawings and Examples, the present invention is further described, the present invention includes but be not limited only to following embodiment.

Suppose that parking garage is the system of a LANDMARC framework, have in system reader (Reader) M (generally M >=3) being evenly arranged, reference label (rf_Tag) is N number of, label to be positioned (Tag) L.Reader energy grade is divided into 1-8 level; Reference label position coordinates is known, is used for auxiliary positioning to improve target labels, i.e. the positioning precision of label to be positioned (Tag).Now, being described below of put forward the methods of the present invention:

(1) defining each label (comprising Tag and rf_Tag) is 8 binary strings, and initialization its each is " 0 ".

(2) every 30s, all readers (Reader) carry out a scan round from 1 to 8 energy levels simultaneously.If certain label is read, just by the r position 1 of corresponding binary string when power grade r by reader j.Write down the binary string matrix that now a N number of reference label and L label to be positioned is corresponding respectively

$R=\left[\begin{array}{cccc}{R}_{11}& R_{12}& ...& R_{1M}\\ R_{21}& R_{22}& ...& R_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ R_{N1}& R_{N2}& ...& R_{\mathrm{NM}}\end{array}\right]---\left(1\right)$

$T=\left[\begin{array}{cccc}{T}_{11}& T_{12}& ...& T_{1M}\\ T_{21}& T_{22}& ...& T_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ T_{N1}& T_{N2}& ...& T_{\mathrm{NM}}\end{array}\right]---\left(2\right)$

Wherein, R _ij(i ∈ (1, N), j ∈ (1, M) represent the binary string that i-th rf_Tag is corresponding with a jth Reader, T _lj(l ∈ (1, L), j ∈ (1, M)) represents the binary string that l Tag is corresponding with a jth Reader.

(3) for certain concrete label Tag_p to be positioned, find out successively from matrix T containing three maximum readers of " 1 ", be designated as Reader_a, Reader_b and Reader_c, and binary string corresponding for these three readers is combined into new matrix

T _p＝[T _paT _pbT _pc] (3)

(4) from matrix R, choose reference label corresponding to reader Reader_a, Reader_b and Reader_c and binary string, remove full zero row, form new matrix (supposing there be x reference label, 1≤x≤N)

$R^{\′}=\left[\begin{array}{ccc}{R}_{1a}^{\′}& R_{1b}^{\′}& R_{1c}^{\′}\\ R_{2a}^{\′}& R_{2b}^{\′}& R_{2c}^{\′}\\ .& .& .\\ .& .& .\\ .& .& .\\ R_{\mathrm{xa}}^{\′}& R_{\mathrm{xb}}^{\′}& R_{\mathrm{xc}}^{\′}\end{array}\right]---\left(4\right)$

(5) by matrix T _pcarry out step-by-step AND operation with the corresponding element in R ', its matrix of consequence is designated as

(6) by matrix T R ' often row in complete zero binary string reset, the set of non-full zero binary string, forms new matrix T R _p.

(7) selected k value (general k>=4), compute matrix TR _pthe often number of row 1, gets the reference label of the capable representative of front k as " nearest-neighbors " from big to small according to the number of every row 1.

Here, if k value is 1, get the reference label that first three signal intensity is maximum, obtain their center-of-mass coordinate, then calculate this barycenter with point coordinate between the maximum reference label of signal intensity, in this, as the final position of label to be positioned; When k value is 2, in two reference label that selected signal intensity is maximum, point coordinate is as the final position of label to be positioned.

(8) utilize " nearest-neighbors " reference label coordinate, calculate the position coordinates of label to be positioned

$(x,y)=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{w}_i(x_i,y_i)---\left(6\right)$

Here w _ifor the weight shared by reference mark.From tag distances to be positioned more close to then shared larger (the i.e. TR of weight _pin the number reference label weight that this row is corresponding more at most of every row 1 larger).The present invention adopts compared to the easier account form of LANDMARC location algorithm, i.e. w _ibe in the i-th row 1 number account for selected k capable in 1 the number percent of number.

(9) repeat above (3) ~ (8) step, calculate the position of all labels undetermined.

The present embodiment builds the Indoor Simulation environment of a 16m*16m, and the layout of reader and reference label as shown in Figure 2.From left to right, from top to bottom, reader numbering is followed successively by 1-9.

Utilize matlab R2012a version simulation software to the inventive method and LANDMARC method, carry out tag location Contrast on effect to be positioned emulation.Here k=4 is made, random generation 500 labels to be positioned.Simulation process is as follows:

1) defining also each label of initialization is the binary string of 8 complete " 0 ";

2) every 30s, all readers (Reader) carry out a scan round from 1 to 8 energy levels, write down the binary string matrix T that now reference label R and label to be positioned are corresponding respectively;

3) for certain concrete label Tag_p to be positioned, find out from matrix T containing three maximum readers of " 1 ", and binary string corresponding for these three readers is combined into new matrix T p;

4) from matrix R, choose the binary string of the reference label that three readers corresponding to Tp read, remove full zero row, form new matrix R ';

5) corresponding element in matrix T p and R ' is carried out step-by-step AND operation, obtain matrix T R ';

6) by matrix T R ' often row in complete zero binary string reset, the set of non-full zero binary string, forms new matrix T R _p;

7) TR is calculated _pthe often number of row 1, gets the reference label of the capable representative of front k as " nearest-neighbors " from big to small according to the number of every row 1;

8) utilize " nearest-neighbors " reference label coordinate, calculate the position coordinates of this label to be positioned according to formula (6);

9) repeat above (3) ~ (8) step, calculate the position of all 500 labels undetermined, and calculate its positioning error and error accumulation distribution;

11) utilize LANDMARC method, calculate the position coordinates of all 500 labels undetermined and positioning error thereof and error accumulation distribution.

Positioning error is the difference of required coordinate and Tag actual coordinate, is

$e=\sqrt{{(x-x_0)}^2+{(y-y_0)}^2}---\left(7\right)$

Wherein, (x ₀, y ₀) be the actual coordinate of Tag; (x, y) coordinate for being calculated by the inventive method or LANDMARC method.Two kinds of methods to the final error cumulative distribution of 500 tag location to be positioned as shown in Figure 3.

In Fig. 3, horizontal ordinate x is error amount, and ordinate F (x) then represents the deviation accumulation distribution under error x.As seen from Figure 2, the method that the present invention proposes, compared with former LANDMARC algorithm, not only effectively reduces maximum positioning error, and improves entire system positioning precision.

Claims (1)

1. a car method is sought in the parking garage based on location, Delta Region, it is characterized in that comprising the steps:

(1) build the positioning system of a LANDMARC framework, have reader M that is evenly arranged in system, M >=3, the reference label that position coordinates is known is N number of, and reader energy level is divided into 1-8 level;

(2) define each label to be positioned and reference label is 8 binary strings, initialization each be 0;

(3) every 30s, all readers carry out a scan round from 1 to 8 energy levels simultaneously; If certain label to be positioned is read, just by the r position 1 of corresponding binary string when power grade r by reader j; Write down the binary string matrix of now N number of reference label respectively $R=\left[\begin{array}{cccc}{R}_{11}& R_{12}& ...& R_{1M}\\ R_{21}& R_{22}& ...& R_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ R_{N1}& R_{N2}& ...& R_{\mathrm{NM}}\end{array}\right]$ The binary string matrix corresponding with L label to be positioned $T=\left[\begin{array}{cccc}{T}_{11}& T_{12}& ...& T_{1M}\\ T_{21}& T_{22}& ...& T_{2M}\\ .& .& & .\\ .& .& & .\\ .& .& & .\\ T_{L1}& R_{L2}& ...& T_{\mathrm{LM}}\end{array}\right],$ Wherein, R _ijrepresent the binary string that i-th reference label is corresponding with a jth reader, T _ljrepresent the binary string that l label to be positioned is corresponding with a jth reader, i ∈ (1, N), l ∈ (1, L), j ∈ (1, M);

(4) for certain concrete label Tag_p to be positioned, find out successively from matrix T containing 1 three maximum readers, be designated as Reader_a, Reader_b and Reader_c, and binary string corresponding for these three readers is combined into new matrix T _p=[T _pat _pbt _pc];

(5) from matrix R, choose reference label corresponding to reader Reader_a, Reader_b and Reader_c and binary string, remove full zero row, form new matrix $R^{\′}=\left[\begin{array}{ccc}{R}_{1a}^{\′}& R_{1b}^{\′}& R_{1c}^{\′}\\ R_{2a}^{\′}& R_{2b}^{\′}& R_{2c}^{\′}\\ .& .& .\\ .& .& .\\ .& .& .\\ R_{\mathrm{xa}}^{\′}& R_{\mathrm{xb}}^{\′}& R_{\mathrm{xc}}^{\′}\end{array}\right],$ X indicates x reference label;

(6) by matrix T _pcarry out AND operation bit-by-bit with the corresponding element in R ', its matrix of consequence is designated as

(7) by matrix T R ' often row in complete zero binary string set to 0, non-full zero scale-of-two tandem arrangement 1, forms new matrix T R _p;

(8) compute matrix TR _pthe often number of row 1, gets the reference label of the capable representative of front k as nearest-neighbors from big to small according to the number of every row 1; K>=4;

(9) coordinate (x of nearest-neighbors is utilized _i, y _i) calculate the position coordinates of label to be positioned wherein, w _ibe in the i-th row 1 number account for selected k capable in 1 the number percent of number;

(10) repeat step (4) ~ (9), calculate the position of all labels undetermined.