Wenguang Mao Jian He Lili Qiu UT Austin MobiCom 2016 Why motion tracking Motionbased Games Virtual Reality Why motion tracking Support motionbased interaction Smart Appliance Possible solutions ID: 661196
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CAT: High-PreCision Acoustic Motion Tracking
Wenguang Mao, Jian He, Lili Qiu
UT Austin
MobiCom
2016Slide2
Why motion tracking?
Motion-based Games
Virtual RealitySlide3
Why motion tracking?Support motion-based interaction
Smart ApplianceSlide4
Possible solutions
Vision
based approach
Needs extra hardwareDepends on lighting conditionComputationally heavySlide5
Possible solutions
RF
based approach
WiFi : limited accuracy (e.g., 10 cm [Chronos16])RFID: limited accuracy (e.g., 4 cm [RF-Idraw])60 GHz waves: extra hardware not widely available 60GHz AntennaSlide6
Acoustic Signal
Slow propagation – helpful to achieve
high accuracy
Easily available speakers and mics –
widely available
Low sampling rate – feasible for
SW processingSlide7
CAT
CATSlide8
Key Components
Distributed FMCW
Doppler Shift
Optimization Framework
Audio Samples
Movement Trajectory
Distance
Velocity
CATSlide9
FMCWFMCW for propagation delay estimation
Less bandwidth usage than using a sharp pulse
Send a chirp whose freq. changes linearly over time
Estimate the frequency difference
, and
~ distance travelled by the chirp
Slide10
Distributed FMCWSpeaker (sender) and microphone (receiver):Not known when the chirp is sent Two-step distance estimation
Sampling rate offset
Drift compensation
Time
Frequency
Transmitted
ReceivedSlide11
Two-Step Distance EstimationDecompose distance
into two parts
Pseudo-transmission time
Reference pointSlide12
Two-Step Distance EstimationDecompose distance
into two parts
Pseudo-transmission time
Reference pointSlide13
Pseudo-Transmission Time
Time
Frequency
Transmitted
Received
Pseudo-Transmitted
Slide14
Two-Step Distance EstimationDecompose distance
into two parts
Pseudo-transmission time
Reference pointSlide15
Reference Point
Doppler +
Doppler -Slide16
Drift Compensation
Estimated distance drift over timeSlide17
Drift CompensationDue to imperfect clocks, the sender and the receiver have different the sampling ratesE.g., 44100.1 Hz (sender), 44099.9 Hz (receiver)
1764 samples at the receiver
1764 samples at the sender
Prop. delay
Chirp 1
Prop. Delay
Chirp 2
Chirp diff.Slide18
Drift CompensationSlide19
Drift CompensationSlide20
Doppler Shift Measurement
Measure frequency shift
between transmitted and received signals
Velocity is given by
Slide21
Optimization frameworkFusing distance and velocity measurementsFind position
that fits the measurements best
Efficient algorithm for solving it
Incorporate IMU measurements
Dist. measurement fitting error
Vel. measurement fitting error
Multiple tracking periods
Smooth the estimated results
No error accumulationSlide22
Experiments2D tracking with 2 speakers2D tracking with 3 speakers
3D tracking with 4 speakersSlide23
2D Tracking Accuracy
CAT is accurate and fusing distance/velocity significantly improves the performance
6mm
8 cm
2 cm
Slide24
3D Tracking
8-9 mm 3D tracking errorSlide25
User Study
(a) CAT
(b)
AAMouse
(Doppler only)
4mm trace error
easy to use
Red: reference
Blue: traced by usersSlide26
ConclusionDistributed FMCW to support a separate sender and receiverOptimization framework and algorithm to fuse distance and velocity over time
CAT tracking system
Achieves mm-level accuracy on commodity devices
Future work: develop new applications