A Novel RFID tag Positioning Method Based on

Mobile RFID Reader and Vehicle-mounted GNSS

Changfeng Jing1,2

*, Mingyi Du1,2

, Likun Shang1,2

, Jiawen Wang3

1School of Geomatics and Urban Spatial Information of Beijing University of

Civil Engineering and Architecture, Beijing, China 2Key Laboratory for Urban Geomatics of National Administration of Surveying,

Mapping and Geoinformation, Beijing, China 3CCCC Water Transportation Consultants Co., LtdNo.28 Guozijian St.

Dongcheng District,Beijing, 100007, P. R. China

*Corresponding author, e-mail: jingcf@bucea.edu.cn

Abstract—It causes lots of trouble for the managers in the

department of urban management to manage the urban

components because of the mobility of some urban components

such as breakfast cart, stalls, and newsstands. To resolve this

problem, the key issue is that how to get locations of these

components rapidly and conveniently. Although, GPS is the

popular positioning system used in the outdoors, urban buildings

and other objects, such as trees, weaken the GPS signal and

decrease the positioning precise. With the Internet of Thing (IOT)

development, RFID is a better way for locating. In traditional

applications, many RFID readers or reference tags must be

deployed to being a network for calculating coordinates of target

objects. This has pitfalls of poor application in urban complex

environment, expensive cost, and difficulty to maintenance. This

paper presents a new method based on mobile RFID reader and

vehicle-mounted Global Navigation Satellite System (GNSS) to

locate the mobile urban components. The method needs RFID tag

pasted on mobile urban component. The cost is lower in this way.

When the tag falls within the detecting range of RFID reader, the

coordinate can be calculated immediately. This kind of

collaboration locating is a novel method for positioning by

combining mobile RFID reader and vehicle-mounted GNSS. An

experiment is conducted and proved that this proposed approach

is valid for positioning of mobile urban components.

Keywords-collaboration positioning; mobile RFID reader;

vehicle-mounted Global Navigation Satellite System (GNSS)

I. INTRODUCTION

Context-awareness, and, in particular, location-awareness, is, according to Gartner Inc., one of the key technologies in the next few years [1] and the crucial factor of sophisticated location-based services (LBS). The challenges of providing information about the current location are multifaceted.

In urban component management, the locations of most urban components are fixed, but there are a few non-fixed urban components which may be moved from here to there such as breakfast Cart and newsstand. Because of their mobility features of them, the locations that the roadside stalls occupy would impact traffic to some extent. The random shifting of stalls also impact city appearance. These have becoming an increasingly important issue. It is a continuous

scientific research issue how to locate the site and get evidence for supervision. At the same time, it is an issue concerned mostly by local department of urban management. In traditional IOT (Internet of Thing) technology, the RFID tag coordination is jointed computed by fixed RFID reader network with known nodes’ coordination [2][3][4]. Thus, the network must be coverage of almost all areas around the city when this technique is used in whole city. This is much more expensive.

In this paper, a novel method is proposed for mobile tag locationing based on Mobile RFID Reader and Vehicle-mounted GNSS. This paper makes a brief introduce about RFID location in section II. Our proposed method is presented in section III and experiment analysis is in section IV. Finally, some conclusions are given in section V.

II. OVERVIEW OF RFID LOCATION

Tracking RFID tags is an inherent function of the RFID system, where the reader is employed to activate nearby tags and report their existence (and perhaps their contents as well). Such an approach can usually detect the target tags when they approach strategic locations only, where the readers are deployed.[5] Jeffrey divided RFID location system into two categories: position and tracking.[6] The former provides the means to determine location, and the latter monitor objects in their purview without involving the target in the computation. In [5], Jeffrey paid attention to the mixed application of two types and named it “location sensing”. In [5], Chong gives another category: passive schema and active schema by the target RFID sensor type. In the former, RFID tag is located by many RFID reader, otherwise, in active schema, RFID reader is located by around RFID tags.

A location sensing prototype system, called LANDMARC (LocAtionNiDentification based on dynaMic Active Rfid Calibration), is presented in [7]. The main idea of LANDARC is to deploy many reference RFID tags as different graphic structure and small RFID readers. Based on signal strength information of RFID reader, a k-nearest neighbor approach is taken to estimate the location of the target tag. However, these approaches can only provide coarse location information.

Supported by Beijing Natural Science Foundation (8122017, KZ201210016016) and the General Program of Science and Technology

Development Project of Beijing Municipal Education Commission of

China(KM201110016004) and The National Key Technology R&D Program(2012BAJ14B03).

Global Navigation Satellite System (GNSS) as a satellite-based navigation system gives an overall world coverage, low cost, and is easy to use. The Global Positioning System (GPS) of America is the most popular GNSS, which made up of a network of 24 satellite placed into orbit [8]. GPS is widely used to track moving objects located outdoors. However, GPS, as it is satellite dependent, has an inherent problem of accurately determining the location of objects located inside dense buildings in city [9].

III. THE PROPOSED RFID TAG POSITIONING METHOD

In urban management, some urban components have mobility, and moved from here to there, which causes a big trouble for the managers in department of urban management. In grid urban managerialism, the discovery of urban components event is depended hardly on city inspectors. The low efficiency of events’ discovery is partially caused by the positioning of urban components manually. With the introduction of Internet Of Thing (IOT), RFID is helpful for the location of urban components. The fixed tag location is easy, technically. Otherwise, mobile tag is the research hotspot. In some related researches and applications, the RFID tag coordination is united computed by fixed RFID reader network with known node coordination [2][3][4]. Thus, it is must be coverage all around the city when this technical is used in whole city. This is much more expensive.

In this research, our objective is to locate the mobile urban components such as city breakfast carts, newsstands equipped RFID tags. Comparing traditional methods, deploying many fixed RFID readers or tags, we used both the mobile RFID readers and vehicle-mounted GNSS for locating.

A. Locating devices

The location system is composed of GPS module and RFID module. The former gets the RFID module coordinate and the latter used to locate target RFID tag. The GPS module includes GPS antenna, GPS mainboard, GPS data acquisition system, shows as Fig 1a. Fig 1b presents the RFID reader and Fig 1c are RFID tags. RFID readers and tags constitute the RFID module.

(a)

(b) (c)

Figure 1. Pictures of GPS module (a) and RFID module (b,c)

B. The principle of location

In traditional location methods, many RFID readers or tags composed the RFID network which is more expensive and has difficulty in device maintenance. In our research, the mobile RFID reader is employed to simulate virtual RFID readers. This is the core of our proposed method.

First, the target object is equipped with a RFID tag which is low cost. Second, when the target falls in the range of RFID, reader continuous gets the signal and calculates the range between reader and tag. With the mobility of RFID reader, we can get several ranges of different reader positions in very short time. As shown in Figure 2, position A, B, C are different positions that are within the range of one same RFID reader, which can be regarded as three fixed RFIDs at different locations.

Figure 2. Principle of location

Our objective is to obtain the coordinate of target. In above content, we get the distance from A to P as shown in Fig.3, called da, and the distance form B to P, called db.

Figure 3. graphic relation of several important points

Therefore, we get two formulas as the follow:

(xp - xa)2

+ (yp - ya)2

= da2

(1)

(xp - xb)2

+ (yp - yb)2

= db2

Where, (xa,ya), (xb,yb) is the coordinate of position A and position B respectively. The coordinate of A and B can be acquired from GPS module and regarded as known parameters. Thus, the coordinate of P can be calculated through mathematics solution.

IV. EXPERIMENT

A. Study Area and schema design

An experiment is designed to validate the proposed approach with our method. The experiment address and test time are the most important and are representative elements in our experiment. 200m line roads are selected as our study area, and 10:00am is our experiment time. A series of distance points, range data are collected in Xicheng district in Beijing.

The results of our experiment are influenced largely by the precise of Vehicle-mounted GPS. So, the first step is to determine the precise of GPS. The second, the range precise between RFID reader and tag must be evaluated. The third, a vehicle with 60KM/h is used to collect experiment data.

B. Experiment and Data collection

In estimation of GPS precise, the point coordinates measured by Leica GPS are regarded as the true value. We compared the vehicle-mounted GPS data and the Leica GPS data to determine the precise. Furthermore, we import the precise factor into the calculating of target tag coordinate.

In the estimation of range precise, we compare the reference value by electronic distance measuring instrument and measured RFID range data. This factor is taken into account in tag location.

With this vehicle, 20 group data with intervals of 10m are collected in a road with length of 200m,. The range data are shown in table 1. The coordinates of tags are shown in table 2.

TABLE I. RANGE EXPERIMENT DATA

Preset

range(

m)

Measur

ed

range(

m)

Difference(

∆)

Preset

range(

m)

Measur

ed

range(

m)

Difference(

∆)

10 10.13 +0.13 110 107.49 -2.51

20 19.93 -0.07 120 119.10 -0.80

30 29.90 -0.10 130 127.23 -2.77

40 38.89 -1.11 140 142.07 +2.07

50 51.32 +1.32 150 152.93 +2.93

60 60.99 +0.99 160 160.54 +0.54

70 72.10 +2.10 170 174.10 +4.10

80 78.73 -1.27 180 185.58 +5.58

90 88.32 -1.68 190 194.38 -4.38

100 102.24 +2.24 200 203.65 +3.65

The comparing of range experiment data and standard value is shown in Table1. From table data, we can draw a conclusion that the difference in [-3m, +3m] when the threshold range is within 160m.

TABLE II. CALCULATED COORDINATE DATA

No. Calculate value difference Closing

error（m） (X) （Y） (△ X) (△ Y)

1 498846.6 307259.0 -0.906 3.375 3.49569

2 498849.2 307257.6 1.718 2.001 2.63706

3 498849.1 307257.7 1.625 2.062 2.62574

4 498847.0 307258.7 -0.503 3.125 3.15918

5 498846.6 307259.0 -0.906 3.375 3.49455

6 498849.2 307257.6 1.718 2.004 2.63706

7 498849.1 307257.7 1.625 2.062 2.62574

8 498847.0 307258.7 -0.501 3.125 3.15981

9 498848.5 307254.5 1.014 -1.093 1.48198

10 498854.7 307256.9 7.218 1.281 7.33157

11 498851.6 307256.2 4.093 0.562 4.13222

12 498848.9 307254.8 1.406 -0.812 1.62409

13 498851.3 307256.2 3.843 0.593 4.26685

14 498849.7 307259.2 2.254 3.625 4.26658

15 498848.2 307254.5 0.751 -1.061 1.30054

16 498848.7 307254.8 1.254 -0.781 1.47472

17 498850.1 307255.3 2.593 -0.312 2.61288

18 498847.8 307254.3 0.375 -1.281 1.33528

19 498849.1 307255.0 1.656 -0.625 1.76678

20 498851.4 307255.4 3.937 -0.156 3.94059

The comparing of two groups of data is shown in Table 2. From this table, we see the difference falls in [-5m, +5m] when the distance between RFID reader and tag falls in 200 meter. In Table 2, one big closing error is +7.33m, the reason caused this low precision is that the line-of-sight is blocked by a bus.

A

B

C

P

Vehicle route

RFID reader position Tag position

RFID reader position

RFID reader position

V. CONCLUSIONS

Comparing our method with those existed in current researches and applications, the collaboration location based on mobile RFID reader and vehicle-mounted GNSS is a novel idea. It can resolve the dependence of RFID reader network, and substantially reduce the investment on hardware. It may rich and extent the theory of positioning based on RFID in factor and impacting mechanism. The result of our study indicates that this method would be real-time locating the mobile urban components and can be enforce the law with precise data. Thus the collaboration location method can meet the requirement of intelligent and precise urban management.

In our test, a few of working environments with high obstructions such as building corners and vehicle velocity that affect the precise of collaboration location. For velocity, we get a thread hold value for certain measure accuracy, but for environment factor cannot get the right value for workflow. This is our future research. With the increasing number of tests, we conclude that the time of making measurement has effects on accuracy. Thus, in real applications, we suggest that it is better to measure twice. Another important finding is that an adaptive algorithm must be developed to select the enough GNSS location points for calculation. It can be helpful to get a good efficiency in positioning.

ACKNOWLEDGMENT

The authors would like to express appreciations to colleagues in our laboratory for their valuable comments and other helps.

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