Transcript Macro-Calibration in Sensor/Actuator Networks Kamin Whitehouse, David Culler Problem • Individual sensor calibration in a large sensor network is not feasible • Sensors difficult to.

Macro-Calibration in
Sensor/Actuator Networks
Kamin Whitehouse, David Culler
Problem
• Individual sensor calibration in a large
sensor network is not feasible
• Sensors difficult to calibrate because of a
lack of a calibration interface
Calibration Techniques
• Traditional calibration
– Parameters belong to transmitter/receiver pair
• Iterative calibration
– Calibrate receivers against a reference transmitter
– Suffers from error propagation
– Assumes reference is calibrated well, error is in uncalibrated device
• Mean calibration
– Calibrate receivers against all transmitters
– Does not allow calibrate both receivers and transmitters
– Avoids separation problem by not calibrating transmitters
• Separation Problem
– Inability to distinguish receiver effects from transmitter effects
Joint Calibration
• Looks at system as a whole
• Technique
– Parameterize each device and model system
response
– Collect data from system
– Choose parameters such that system performance is
optimized
• Previous techniques optimize individual device
response
• Only need to use system output to calibrate –
don’t need to directly observe actual response.
– Ex. In localization, only need distance estimates
Calimari
• MICA motes
• Uses RSSI and acoustic TOF ranging
Experiments
• 32 MICA motes in grid on table 210cm x
90cm
• Each node generated up to 31 distance
estimates
• Average error after uniform calibration
(linear regression) 21%
• Iterative: 19.7%, Mean: 16.0%
• Joint: 10.1%
Auto Calibration
• Use information about application to help
calibration process
• Localization:
– dij = dji
– dij + djk – dik >= 0
– Can use these to help constrain problem
• -
Comments
• Not truly adhoc yet
• Where is computation performed?
• Accuracy of calibration vs. number of
estimates