A Hybrid Method for achieving High Accuracy and Efficiency in Object Tracking using Passive RFID
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Transcript of A Hybrid Method for achieving High Accuracy and Efficiency in Object Tracking using Passive RFID
A Hybrid Method for achieving High A Hybrid Method for achieving High Accuracy and Efficiency in Object Tracking Accuracy and Efficiency in Object Tracking
using Passive RFIDusing Passive RFID
Lei Yang1, Jiannong Cao1, Weiping Zhu1, and Shaojie Tang2
1Hong Kong Polytechnic University, Hong Kong2Illinois Institute of Technology, USA
OutlineOutline
Introduction
Existing Approaches
Our Approach
Evalution
Conclusions
MotivationMotivation
Technical DifficultiesTechnical DifficultiesReal-time characterstic
Tracking is more difficult than localization of stationary objects because executiion the algorithm needs to be finished before a deadline
Noisy measurementRFID reading is noisy, which means the tags have low probability to be detected by the reader even though they are within the object’s reading range
Constrained computional resource on the mobile RFID devices
Problem DefinitionProblem DefinitionGiven
K tags deployed in the enrionment
The location of the i-th tag Ti
The RFID reader scans frequency f
The reader’s reading range is tr , which can be adjusted
The RFID reading at time k
AssumeThe reader has a probability p(r) to read the tags within its reading range
ObjectiveEstimate the continuous locations of the mobile object using the uncertain RFID readings
H
tr
Antenna
Tags
d
v
1{ }i Kk k iz r
, ( )
0,
re r trp r
r tr
Existing ApproachesExisting Approaches
Centroid Localization (CL) [N.Bulusu 2000]
Average the locations of all the tags that have been detected by the RFID readerThe tracking problem is solved by executing CL periodicallyLow accuracy in case of low detecting probability
Weighted Centroid Localization (WCL)Improve the accuracy by assigning weights in averaging the tags’ locationEach tag’s weight equals to the times that the tag has been detected in past N scansLarge error if the object’s speed is large relative to the scanning speed of the RFID reader
Both methods are computationally cheap
Estimated Location
Estimated Location
Existing ApproachesExisting Approaches
Centroid Localization (CL) [N.Bulusu 00]
Average the location of all the tags that have been detected by the RFID readerThe tracking problem is solved by executing CL periodicallyLow accuracy in case of low detecting probability
Weighted Centroid Localization (WCL) [Behnke08]
Improve the accuracy by assigning weights in averaging the tags’ locationEach tag’s weight equals to the times that the tag has been detected in past N scansLarge error if the object’s speed is large relative to the scanning speed of the RFID reader
Both methods are computationally cheap
• Count the detection times for each tag in recent 5 scans;• The weight of each tags is equal to the count number.
t = 1
t = 2
t = 3
t = 4
1 4 2
1 3 2
Estimated Location
t = 5Detection times
v
• WCL has large error if the object’s speed is large relative to the scanning speed of the RFID reader .
Existing ApproachesExisting Approaches
Centroid Localization (CL) [N.Bulusu 00]
Average the location of all the tags that have been detected by the RFID readerThe tracking problem is solved by executing CL periodicallyLow accuracy in case of low detecting probability
Weighted Centroid Localization (WCL) [Behnke08]
Improve the accuracy by assigning weights in averaging the tags’ locationEach tag’s weight equals to the times that the tag has been detected in past N scansLarge error if the object’s speed is large relative to the scanning speed of the RFID reader
Both methods are computationally cheap
Existing ApproachesExisting Approaches
Particle Filter [D.Hahnel06 ][Schneegans07] ][Vorst08]
The object’s location is calculated by averaging a set of particles
Each particle represents a random location sample, and has a weight in caculating the object’s location
In each iteration the particle evolves through three stepsPrediction - Predict the location of each particle according to its location at previous time and the object’s moving speed
Updating - Update the weight of each particle according to the sensory data
Resampling – Filter out the particles with small weight.
Existing ApproachesExisting Approaches
Particle Filter (PF)
The accuracy is better than CL/WCL, but continuous
execution of particle filter suffers from high computational
cost
PF achieves high accuracy by sacrificing the computational
efficiency
Our ApproachOur ApproachObservations
WCL are efficienct but the accuracy is not good when the object’s speed is large
Particle filter has satisfactory accuracy but is costly
It is usual that the object moves with a varying speed
Can we integrate the two approaches together to achieve better efficiency as well as accuracy?Hybrid Method
Adaptively switch between using WCL and PF according to the estimated velocity of the moving object
When the speed is low, WCL is used; otherwise, PF is used.
Our ApproachOur Approach
H
tr
Antenna
Tags
d
v
Select the optimal reading range tr
Estimate the object’s speed v
WCL Partical Filter
v < vth v > vth
Technical DetailsTechnical Details
Pratical Issues
How to determine the reading range (or power level) of the
reader?
How to estimate the speed of the moving object?
How to determine the threshold for the speed vth?
Technical DetailsTechnical DetailsHow to adjust the reading range tr (power level) ?Density of tags is presented by its spacing aThe otpimal a/tr is 0.9The necessary tr of the RFID reader should be as large as
1.1a
Technical DetailsTechnical DetailsHow to Estimate the object’s speed?
Calculate the time duration di(N) that each tag i stays in the
reader's reading range in the last N time slots ( )
Select the maximum one dmax(N) = max {di} to estimate the
speed
2tr is the diameter of the reading range; c is scaling constant
depending on the tag density ( 0<c<1 )
The tag with largest di tends to be the one which is closest
to the object's actual moving path
max
2
( )
tr cv
d N
iN d i
Technical DetailsTechnical DetailsConsideration of the threshold vth
Threshold of the speed vth is too low, the hybrid method
has little improvement on the computational cost
compared with particle filter
If vth is set too high, the hybrid method sacrifices the
accuracy too much
We can control the tradeoff between accuracy and
efficiency by chosing proper Nth
2th
th
tr fv
N
EvaluationEvaluation
v (m/s) 0.1 0.2 0.3 0.4 0.5 0.6
WCL
(ms)
119 86 75 64 65 66
PF (ms) 7593 8484 10568 9792 9260 9276
Comparison between WCL and PF
Simulation environment’s size is 4m*4m
The object moves with constant speed along a rectangle
trajectory ( a = 0.27m, f=10Hz, tr = 0.3m )
EvaluationEvaluation
How much does the Hybrid Method improve the performance?
The object's velocity varies during the trajectory
Schemes WCL PF Hybrid
Location
Error (m)
0.187 0.068 0.062
Execution
Times (s)
0.08 4.53 1.26
EvaluationEvaluationIndoor wheelchair tracking
RFID tags are densely deployed in a 4m*6m classroom.
The wheelchair moves along a line with a varying speed,
which is 0.1 m/s at the first half , 0.6m/s at the second half.
UHF RFID reader with a circularly polarized antenna
The reader has 8 power levels, we tune it on level 12.
tr = 60cm,
a = 50 cm,
f = 10Hz,
Nth = 40
EvaluationEvaluationIndoor wheelchair tracking
Experimental Results
The hybrid method almost achieve the same accuracy as
PF, but outperforms PF a lot in term of computational cost
Methods WCL PF Hybrid Method
Location Error (m)
0.482 0.186 0.195
Time per step (ms)
0.2 18.1 7.2
ConclusionsConclusions
We proposed a hybrid method for achieving high accuracy and efficiency in object tracking
The hybrid method is suitable for tracking the mobile object which moves with a varying speed
Our method is demonstrated to be more computational efficient than PF while guaranteing the same accuracy with PF
Thank you!!