SAW-Based RFID for NASA Ground Facilities and Planetary Habitats Patrick W. Fink/Richard Barton October 13, 2008.

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