1. Efforts in Distributed Arrays for Infrasound Measurements Kevin Dillion Wheeler Howard Doug Shields Jere Singleton Miltec Nov. 3, 2008 Approved for Public Release; Distribution Unlimited

2. 2 Distributed Array Background Distributed arrays average out incoherent wind noise by ~ # of sensors (Pa 2 /Hz), while retaining coherent sound across the array The wind noise is incoherent above a certain frequency based on the sensor spacing (X) F starts working ~ windspeed / (4*X) There is greater than 1/n reduction when aperture (Y) is approx. equal to of wind F dip ~ windspeed/(Y) Spacing = X Aperture = Y > 1 / n 1/n1/n

3. 3 Distributed Array Background Distributed Arrays retain coherent sound across the array, but a limit can be determined where sound can become out-of-phase and be reduced in magnitude The sound magnitude is reduced (by R) based on the aperture of the array (Y) F starts averaging out ~ speed of sound / (Y) Spacing = X Aperture = Y R

4. Distributed Array Co-Located With IMS Pipe Array

5. 5 Co-Located Configurations 2007 comparison provided data for our previous test 2008 should provide wind noise reduction at lower frequencies than the 18m x 18m square array Distributed Array, ~ 70m aperture Miltec 200Hz MB2000 20Hz

6. 6 Co-Located Configurations 2007 comparison test –100 sensors –18x18m grid –2m spacing –200Hz sampling rate 2008 comparison test –96 sensors –70m wagon wheel with 30 o separation –16 sensors per spoke and 4m spacing –200Hz sampling rate

7. 7 Low Wind PSD Comparisons The microbarom magnitudes illustrate data is converted correctly Here in low winds it is possible to see the electronic noise floors for the two arrays The distributed array not only reduces wind noise by 1/n, it also reduces electronic noise by 1/n No noticeable change in noise floors between the two tests

8. 8 Wind Noise PSD Comparisons 2007 We wanted to shift the distributed array reduction left to lower frequencies Windy comparison was misleading due to influence of ground cover 2008 We did shift the distributed array reduction left to lower frequencies The ground cover and wind noise reduction matched more closely 20 to 30 more sensors could have provided even better wind noise reduction matching

9. 9 2008 Wind Noise Correlation There was a mean wind speed of 4.3m/s with gusts near 10m/s The pressures generated on the two arrays due to the wind gusts correlated very well visually

10. 10 2008 Sound Events Interesting events occur in low winds and are detected by both arrays Wagon wheel array nearly matches the single sensor from 1Hz to 3Hz, then the sound begins to become out-of-phase “R” begins to happen at ~ 4Hz due to the large aperture in the previous equation Piñon L2 starts averaging out the sound similarly, but then the resonance occurs R

11. 11 Distributed Array Advantage The arrows indicate the heights of the Peak-to-Peak pressures for the two techniques The black PSD line indicates that time-shifting can uncover higher frequency components

12. 12 Distributed Array Advantage The left plot shows the area average, the right plot shows the time-shifted array average The time-shifting helps uncover sound up to 45Hz for the last peak

13. Efforts for Wireless

14. 14 New Sensor New Wireless Sensor 8V, 250mA solar panel 40Hz sampling rate Accepts 4 porous hoses Detected events discussed previously Has nearly same reduction as dist. array, but without the >1/n due to spacing

15. 15 Conclusions 70m wagon wheel distributed array reduced wind noise similarly (within 5db) of the L2 IMS array at Piñon Flat Time-shifting the array data extracted high frequency sound components Test shows a very good comparison between a 70m IMS array and a 70m wagon wheel distributed array of ~100 sensors Porous hose wireless sensor provided a very good comparison to the IMS and distributed arrays Future work –More geometrical configuration tests for wind noise reduction –24-bit version of the wireless sensor –More measurements with the porous hose wireless sensor –Interface a Miltec sensor to the Smart-24 digitizer