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Chunyi Peng Guobin(Jacky) Shen, Yongguang Zhang, Yanlin Li, Kun Tan Microsoft Research Asia BeepBeep: A High Accuracy Acoustic Ranging System using COTS.

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Presentation on theme: "Chunyi Peng Guobin(Jacky) Shen, Yongguang Zhang, Yanlin Li, Kun Tan Microsoft Research Asia BeepBeep: A High Accuracy Acoustic Ranging System using COTS."— Presentation transcript:

1 Chunyi Peng Guobin(Jacky) Shen, Yongguang Zhang, Yanlin Li, Kun Tan Microsoft Research Asia BeepBeep: A High Accuracy Acoustic Ranging System using COTS Mobile Devices

2 Ranging, basic to localization Many excellent systems – Cricket (Mobicom’00) – RIPS (Sensys’05) – ENSBox (Sensys’06) – … Hardware and algorithmic innovation 2

3 Our motivation Proximity detection between devices – Among portable devices MobiUS (Mobisys’07) – Between portable and non-portable devices Phone to PC, Xbox, Printers, Projectors …

4 The requirement A widely applicable solution – Work on COTS devices No additional hardware (e.g., ultrasound) Pure user space software (no change to OS/driver) – Not dependent on infrastructure Applicable in spontaneous, ad hoc situations – Minimum set of sensors High accuracy!

5 A matter of time measurement Mostly, based on time-of-flight measurement – Distance = speed x time – Sound often chosen Slower speed => less demanding on time accuracy Still, a challenging task – 1 ms error in time = 34 cm error in distance 1 cm ranging accuracy requires 30us timing accuracy – Extremely challenging on COTS/software

6 The root cause of inaccuracy – three uncertainties Clock synchronization uncertainty Sending uncertainty time... t0 = wall_clock(); write(sound_dev, signal);... software issuing command sound leaves speaker unknown delays (software, system, driver, hardware, …) ?... read(sound_dev, signal); t1 = wall_clock();... software aware of arrival sound reaches mic unknown delays (hardware, interrupt, driver, scheduling, …) ? Receiving uncertainty

7 Effects of the sending and receiving uncertainties Example measurement of the lower bound on COTS mobile devices (HP iPAQ rw6828) – Highly fluctuating, appears unpredictable – Easily adds up to 1-2 ms (=> a few feet error) CPU idle CPU heavily loaded

8 Our approach – BeepBeep A simple and effective solution – Each device just needs to emit a sound signal and record them simultaneously – Only require a speaker, a mic, and some way of communicating with the other device Achieving 1cm accuracy while satisfying all the requirements

9 Beepbeep’s basic procedure Device ADevice B D AB =|ETOA A -ETOA B |/2 A’s recordingB’s recording ETOA A ETOA B 1.Device A emits a beep while both recording 2.Device B emits another beep while both continue recording 3.Both devices detect TOA of the two beeps and obtain respective ETOAs 4.Exchange ETOAs and calculate the distance

10 Mathematical derivation t A3 2 nd Beep t B3 t B2 1 st Beep t B1 t A0 t A1 ETOA A ETOA B d B,A +d A,B = c·[(t A3 -t A1 )-(t B3 -t B1 )] +d A,A +d B,B = c·(ETOA A -ETOA B )+d A,A +d B,B d B,A -d A,A = c·(t B1 -t A1 ) d A,B -d B,B = c·(t A3 -t B3 )

11 Key techniques, effects and rationale (I) Self-recording – Record signals from both the other party and itself – Establish the starting reference point of the whole ranging process – Duplex audio channel Two-way sensing – Avoid clock synchronization uncertainty – To capture the ending reference point of the whole ranging process not attempt to capture any system time info

12 Key techniques, effects and rationale (II) Sample counting – Avoid referring to system clocks for timing info – Dedicated A/D converter, w/ fixed sampling rate Achievable precision is determined by the sampling frequency: 0.8cm at 44.1kHz sampling rate Putting together: – Bypass all the three uncertainties by making time measurement irrelevant to system clocks

13 Engineering Challenges (I) Signal Design Good signal design helps detection – Easily detectable in digital recording – Robust against ambient noise – Robust against acoustic distortion Low-fidelity speaker & mic in COTS mobile device – Within hardware capability Most COTS devices have limited voice frequency range Our empirical design (“chirp” sound) – 50ms long, shifting frequency from 2 to 6 kHz

14 Engineering Challenges (II) Signal Detection Algorithm Design Efficient and fast signal detection algorithm – Quickly locate possible signal regions Robust against low SNR – Utilize noise floor to boost SNR Combat multipath effect – Multipath: big issue indoor environment – We derived special algorithm to detect first “sharp peak” signal correlation

15 Engineering Challenges (III) Protocol design – Coordinate two (or more) devices in entire ranging process – Minimize ranging time duration Device form factor – Speaker/mic’s placement affect ranging results Vary from one device model to another – Need calibration to adjust ranging calculation

16 System Implementation Platform: Windows Mobile 5.0 – Sound: “wave” API – Communication: “WinSock” (WiFi or Bluetooth) Software architecture – User-mode dynamic linkable library – As service for other applications Test devices – Dopod838 – HP iPAQ 6828

17 Evaluation  Case-A: Indoor, quiet  Case-B: Indoor, noisy  Case-C: Outdoor, car park entrance  Case-D: Outdoor, subway station 50 runs each setting Expr Setting Operation Range Conf. Level AA(|Err|) cm MA(|Err|) cm A(Std) cm M(Std) cm Case-A4.0m94% Case-B4.0m94% Case-C12m98% Case-D10m92%

18 Summary Identified three uncertainties and mitigated them with three key technologies – Two-way sensing – Self-recording – Sample counting BeepBeep provides a simple ranging solution – Achieves 1cm accuracy – On very basic hardware set – Purely in software (user-space)

19 Thanks! Demo session. Welcome to try BeepBeep! Software downloads:

20 Backup

21 Lower bound of sending and receiving uncertainties


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