SAW-Based RFID for NASA Ground Facilities
and Planetary Habitats
Patrick W. Fink/Richard Barton
October 13, 2008
Contributors
• Phong Ngo
• G. D. Arndt, Ph.D.
• Julia Gross
• Chau Phan
• David Ni, Ph.D.
• John Dusl
• Kent Dekome
• Patrick Fink, Ph.D.
• Timothy Kennedy, Ph.D.
• Richard Barton, Ph.D.
• Greg Lin
• Emal Latifzai
• Robert Williams
• Yasser Haridi
• Kent Byerly, Ph.D. (Spatial Acuity)
• George Studor
• Robert Brocato (Sandia National Laboratories)
Courtesy RFSAW, Inc.
Courtesy AirGATE Technologies
NASA Use of 2.4 ISM SAW-Based RFID
SAW RFID – Sample Waveform
Initial Passive, Wireless Sensor Applications
• Major Challenges
– For NASA sensor applications, often want many tags within interrogator field-of-view
– Ranges > 100 feet are desired for many applications
– Primary SAW material in use is very sensitive to temperature
• Good for temperature sensing, but makes other sensors more challenging
• Combination of these challenges prompted early applications based on:
– Larger aperture interrogators + adaptive digital beamforming
– Temperature sensing applications
Waveform Correlation to Determine Temperatures and IDs
• Measured response– Composite signal from
multiple tags + noise
• Template response• Waveform obtained by a
priori measurement
• Analytically modified by range and temperature
• Correlation matrix formed from measured response and modified template responses
• Need to determine effect of non-zero cross-correlations on temperature and range accuracies
Measured tag delay with temperature
delay
dilation
delay
dilation
Correlation simulation - background
• 40-bit Global SAW Tag (GST) tags from RFSAW, Inc.
• Simulation based on measured tag responses with simulated additive, white Gaussian noise; SNR = 20 dB
• Composite signal formed from summation of 11 tag responses
– All tags have same energy (suspected worst case)
– Tags assumed at different ranges and temperatures
• 2D correlation process
– Straightforward entire waveform correlation
• Suitable for RFID/sensor interrogation in which all IDs are known a priori
– 21 time scale increments representing 105 C range
– 21 time delay increments representing 210 ns range
Correlation simulation – results (11 tags)
Tag 1873 correlated with noise, only.Tag 1873 correlated with composite signal + noise.
Tag 1873 – strongest correlation in population
Successive interference cancellation required
Tag 1858 correlated with Tag 1873 present: false peaks.
Tag 1858 correlated aftersubtracting estimate of Tag 1873:
correct peak is identified.
Tag 1858 – 2nd strongest correlation in 11 tag population
Correlation Simulation Results
• Preliminary error statistics for 11-tag population:
– Error in delay
• Mean: 0.53 ns
• Std. Dev.: 1.5 ns
– Error in dilation
• Mean: -0.09 °C
• Std. Dev.: 0.21 °C
• More simulations and tests required for statistical significance
• Need to determine error dependencies upon number of tags in population
Spatial Diversity to Isolate Sensor Clusters
Collision avoidance plan:
Correlations used to isolate tags within defined clusters
Virtual (digital) beamforming limits collision from adjacent clusters
72-element Interrogation in Anechoic Chamber
Direction of Arrival in Anechoic Environment
Spatial diversity for collision avoidance
[ Before – 2 tag responses – to be added]
[ After – single tag response recovered ]
Operation in KSC Cryogenics Laboratory
Direction-of-Arrival: Two tags in clutter
Applications – Lunar Outpost
• Telemetry– Monitor tool exposure limits: temperature, shock, etc.
– MMOD impact detection and location
– Chemical and atmospheric sensing
RFID Tag
Applications – Lunar Outpost
• Navigation– Lunar landing aids
– Lunar “road signs” or “breadcrumbs”
– Passive tag tracking
RFID Tag Tracking
JSC Chamber A (Vacuum & Thermal Cycle)
Application: Environmental Facility Wireless Sensors
• Adaptive interrogation of wireless temperature and pressure sensors
• Goals: Tlow = 20K; 100s of T-sensors; 10s of pressure sensors
JSC Chamber A T-sensor configuration on inner shroud
Sensor coverage schemes for Chamber A
Coverage from wall-basedinterrogators
Coverage from floor-basedinterrogators
Next Wave of Passive, Wireless Sensor Applications
• Additional Challenges
– Desire to integrate calibrated, passive commercial sensors with SAW devices
• Acceleration, acoustic emission sensors are primary targets
– Still need many tags within interrogator field-of-view and long ranges
– Sample rates significantly higher than our temperature applications: > 10 kHz, compared to 1-3 Hz
SNL Concept to Incorporate Commercial Sensors
Sandia National Laboratory (SNL) concept: FET-loading of SAW IDT with passive sensor driving FET
Interdigital Transducers (IDTs)
Passive sensor types under evaluation: accelerometer, acoustic emission
Application Example: White Sands Test Facility
5
4
3 ... 2 1
Application Example: Monitoring Cryogenic Fill Level
SAW TagTemperatureSensors
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