Transcript Acoustic Target Tracking Using Tiny Wireless Sensor Devices
Acoustic Target Tracking Using Tiny Wireless Sensor Devices
Qixin Wang, Wei-Peng Chen, Rong Zheng, Kihwal Lee, and Lui Sha Dept. of CS, UIUC
Introduction
Context –Delay based sound source locating algorithm, requires large number of redundant sensors for accuracy.
-Tiny wireless sensors to real-world acoustic tracking applications.
–Tracking only impulsive acoustic signals, such as foot steps, sniper shots etc. No concept of tracking motion.
Introduction Challenges: – Partial info at one sensor site – Inaccuracy and unreliability of sensors – Effective use of scarce wireless bandwidth Solutions: – Sensor clustering and coordination – Redundancy for robustness – Quality-driven (QDR) networking. Info. flow oriented v.s. raw data flow oriented.
Introduction
Cluster Head
Scenario
Sensor Router Cluster Head Sink/Pursuer Sink/ Pursuer
System Overview
• System Architecture – Acoustic target tracking subsystem Sensor (mica motes) Cluster Head (mono-board computer) Sensors belong to clusters with singular cluster head.
Cluster head knows the locations of its slave sensors. Raw data gathered from sensors are processed in cluster head to generate localization results
System Overview – Communication Subsystem: route back the reports generated by cluster heads to sink cluster covered area cluster head router (mica motes) Sink
Acoustic Target Tracking Subsystem
• Use RBS Time Synch (
error
30
s
).
• Onset Detection (on sensors) –Small sliding window to compute moving average of acoustic signal magnitude.
–Use threshold to detect onset time
t
0.
–Record one buffer load of data, then post process.
Acoustic Target Tracking Subsystem
• Cross Correlation (to find out delays)
Cluster Head: Detected intersted sound Broadcast sound signature Locate sound src loc.
Slave Sensor: Cross correlation to detect local arrival time Report local arrival time
Acoustic Target Tracking Subsystem • Sound Source Locating & Evaluation of
Quality Rank
(main idea) – Throw away apparently erroneous sensor readings.
– Let
A
= cluster’s monitored area,
sound src location
= arg
p
A
min{|
d
(
p
) -
d s
|}, where
d
(
p
) is the hypothetical sensors’ sound arrival time vector, while
d s
function.
is the actual one. |·| is an error measurement
Acoustic Target Tracking Subsystem – In practice, we cannot check
every
apply a grid with 3 3inch 2 location in granularity onto
A A
, instead, we , and only check those grid points.
–
Quality Rank
= percentage of
d
(
p
)’s elements that falls outside boundary of
d s
.
Communication Subsystem • Quality-driven(
QDR
) Redundancy Suppression and Contention Resolution
– Redundant clusters may report same event’s location. Good for reliability reasons.
– Quality Rank is used to suppress inferior reports and only report high quality rank localization reports to data sink
Acoustic Target Tracking Subsystem – Quality Rank is also used for contention resolution along the routes (with CSMA as MAC) to let higher quality reports get to data sink earlier:
T backoff = QualityRank
interval + random
• Locations of sensors and sound sources in a single cluster
Experiment
Experiment • Examples of localization results for different sound source locations
Experiment • Average error vs. sound source locations. Note sound source is a 4inch speaker
Experiment
Experiment • % of reports within 3 inch error range: higher quality rank, higher creditabi lity
Experiment • Quality driven ( QDR ): Effect of various
interval
on the percen tage of suppressed reports
Experiment • Effect of Quality-driven( QDR ) Suppose info/bit is fixed; the smaller
Quality Rank
, the better the quality.
U k
S Q i k
, where
U k
is the utility of the
k
th packet
S k
is the size of
k
th packet,
Q k
is the Quality Ra nk of
k
th packet.
Conclusion
• Acoustic target tracking using
tiny
wireless devices with satisfying accuracy is possible.
• Quality Rank can be used to decide the quality of tracking result • Quality-driven redundancy suppression and contention resolution is effective in improving the information throughput.