Skip to main content

News about Scitation

In December 2016 Scitation will launch with a new design, enhanced navigation and a much improved user experience.

To ensure a smooth transition, from today, we are temporarily stopping new account registration and single article purchases. If you already have an account you can continue to use the site as normal.

For help or more information please visit our FAQs.

banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
/content/asa/journal/jasa/138/2/10.1121/1.4926900
1.
1. C. B. Hasager, A. Peña, M. B. Christiansen, P. Astrup, M. Nielsen, F. Monaldo, D. Thompson, and P. Nielsen, “ Remote sensing observation used in offshore wind energy,” IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens. 1(1), 6779 (2008).
http://dx.doi.org/10.1109/JSTARS.2008.2002218
2.
2. P. Srinivasulu, P. Yasodha, P. Kamaraj, T. N. Rao, A. Jayaraman, S. N. Reddy, and S. Satyanarayana, “ 1280-MHz active array radar wind profiler for lower atmosphere: System description and data validation,” J. Atmos. Oceanic Technol. 29(10), 14551470 (2012).
http://dx.doi.org/10.1175/JTECH-D-12-00030.1
3.
3. P. Drobinski, P. H. Flamant, and J. Pelon, “ Evidence of organized large eddies by ground-based Doppler lidar, sonic anemometer and sodar,” J. Bound. Layer Meteorol. 88(3), 343361 (1998).
http://dx.doi.org/10.1023/A:1001167212584
4.
4. N. D. Kelley, B. J. Jonkman, G. Scott, and Y. L. Pichugina, “ Comparing pulsed Doppler LIDAR with SODAR and direct measurements for wind assessment,” in WindPower 2007 Conference and Exhibition, Los Angeles, CA (June 3–7, 2007).
5.
5. J. R. Soddell, K. McGuffie, and G. J. Holland, “ Intercomparison of atmospheric soundings from the aerosonde and radiosonde,” J. Appl. Meteorol. 43(9), 12601269 (2004).
http://dx.doi.org/10.1175/1520-0450(2004)043<1260:IOASFT>2.0.CO;2
6.
6. G. Holland, P. Webster, J. Curry, G. Tyrell, D. Gauntlett, G. Brett, J. Becker, R. Hoag, and W. Vaglienti, “ The Aerosonde robotic aircraft: A new paradigm for environmental observations,” Bull. Am. Meteor. Soc. 82(5), 889901 (2001).
http://dx.doi.org/10.1175/1520-0477(2001)082<0889:TARAAN>2.3.CO;2
7.
7.Vaisala, RS80 Radiosonde and WS80 Windsonde Users' Guide ( Vaisala, Hawthorn, Victoria, Australia, 2000).
8.
8. W. Munk and C. Wunsch,“ Ocean acoustic tomography: A scheme for large scale monitoring,” J. Deep Sea Res. Part A. Ocean. Res. 26(2), 123161 (1979).
http://dx.doi.org/10.1016/0198-0149(79)90073-6
9.
9. R. W. Brown, Y.-C. N. Cheng, E. M. Haacke, M. R. Thompson, and R. Venkatesan, Magnetic Resonance Imaging: Physical Principles and Sequence Design, 2nd ed. ( Wiley and Sons, Hoboken, NJ, 2014), Vol. 201, 944 pp.
10.
10. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging ( Society for Industrial and Applied Mathematics, Philadelphia, 2001), 327 pp.
11.
11. R. R. Stewart and S. N. Domenico, Exploration Seismic Tomography: Fundamentals ( Society of Exploration Geophysicists, Tulsa, OK, 1991), 190 pp.
12.
12. K. D. Wilson and D. W. Thomson, “ Acoustic tomographic monitoring of the atmospheric surface layer,” J. Atmos. Ocean. Technol. 11(3), 751769 (1994).
http://dx.doi.org/10.1175/1520-0426(1994)011<0751:ATMOTA>2.0.CO;2
13.
13. A. Ziemann, K. Arnold, and A. Raabe, “ Acoustic travel time tomography—a method for remote sensing of the atmospheric surface layer,” J. Meteorol. Atmos. Phys. 71(1–2), 4351 (1999).
http://dx.doi.org/10.1007/s007030050042
14.
14. K. Arnold, A. Ziemann, and A. Raabe, “ Acoustic tomography inside the atmospheric boundary layer,” Phys. Chem. Earth, Part B: Hydrol., Oceans Atmos. 24(1), 133137 (1999).
http://dx.doi.org/10.1016/S1464-1909(98)00024-0
15.
15. I. Jovanovic, L. Sbaiz, and M. Vetterli, “ Acoustic tomography for scalar and vector fields: Theory and application to temperature and wind estimation,” J. Atmos. Ocean. Technol. 26(8), 14751492 (2009).
http://dx.doi.org/10.1175/2009JTECHA1266.1
16.
16. D. Wilson, A. Ziemann, V. E. Ostashev, and A. Voronovich, “ An overview of acoustic travel-time tomography in the atmosphere and its potential applications,” Acustica 87(6), 721730 (2001).
17.
17. S. N. Vecherin, V. E. Ostashev, and D. K. Wilson, “ Three-dimensional acoustic travel-time tomography of the atmosphere,” Acustica 94(3), 349358 (2008).
http://dx.doi.org/10.3813/AAA.918042
18.
18. S. N. Vecherin, V. E. Ostashev, G. H. Goedecke, D. K. Wilson, and A. G. Voronovich, “ Time-dependent stochastic inversion in acoustic travel-time tomography of the atmosphere,” J. Acous. Soc. Am. 119(5), 25792588 (2006).
http://dx.doi.org/10.1121/1.2180535
19.
19. S. N. Vecherin, V. E. Ostashev, A. Ziemann, D. K. Wilson, K. Arnold, and M. Barth, “ Tomographic reconstruction of atmospheric turbulence with the use of time-dependent stochastic inversion,” J. Acous Soc. Am. 122(3), 14161425 (2007).
http://dx.doi.org/10.1121/1.2756798
20.
20. S. N. Vecherin, V. E. Ostashev, D. K. Wilson, and A. Ziemann, “ Time-dependent stochastic inversion in acoustic tomography of the atmosphere with reciprocal sound transmission,” J. Meas. Sci. Technol. 19(12), 125501 (2008).
http://dx.doi.org/10.1088/0957-0233/19/12/125501
21.
21. M. Barth and A. Raabe, “ Acoustic tomographic imaging of temperature and flow fields in air,” J. Meas. Sci. Technol. 22(3), 035102 (2011).
http://dx.doi.org/10.1088/0957-0233/22/3/035102
22.
22. S. Kolouri and M. R. Azimi-Sadjadi, “ Acoustic tomography of the atmosphere using unscented Kalman filter,” in Proceedings of the 20th European Signal Processing Conference (EUSIPCO) (2012), pp. 25312535.
23.
23. J. L. Spiesberger and K. M. Fristrup, “ Passive localization of calling animals and sensing of their acoustic environment using acoustic tomography,” Am. Natural. 135, 107153 (1990).
http://dx.doi.org/10.1086/285035
24.
24. V. Ostashev, A. Voronovich, and D. K. Wilson, “ Acoustic tomography of the atmosphere,” in IEEE Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS) (2000), pp. 11861188.
25.
25. V. Ostashev, S. N. Vecherin, D. K. Wilson, A. Ziemann, and G. H. Goedecke, “ Recent progress in acoustic tomography of the atmosphere,” IOP Conf. Ser. Earth Environ. Sci. 1, 012008 (2008).
http://dx.doi.org/10.1088/1755-1315/1/1/012008
26.
26. B. G. Ferguson and K. W. Lo, “ Turboprop and rotary-wing aircraft flight parameter estimation using both narrow-band and broadband passive acoustic signal-processing methods,” J. Acoust. Soc. Am. 108(4), 17631771 (2000).
http://dx.doi.org/10.1121/1.1286150
27.
27. A. Finn and S. Franklin, “ Acoustic sense and avoid for UAV's,” in IEEE Proceedings of the 7th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) (2011), pp. 586589.
28.
28. A. Finn, K. Rogers, J. Meade, and S. Franklin, “ Acoustic atmospheric tomography using multiple unmanned aerial vehicles,” in Proceedings of SPIE Remote Sensing Conference (2014), pp. 92420Q92420Q-8.
29.
29. K. Rogers and A. Finn, “ Frequency estimation for 3d atmospheric tomography using unmanned aerial vehicles,” in Proceedings of the IEEE 8th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (2013), pp. 390395.
30.
30. V. Ostashev, Acoustics in Moving Inhomogeneous Media ( Thomson Science, London, 1997), pp. 1261.
31.
31. A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing ( Prentice-Hall, Englewood Cliffs, NJ, 1975), pp. 532571.
32.
32. T. Wiens and P. Behrens, “ Turbulent flow sensing using acoustic tomography,” in Proceedings of Inter-Noise 2009: Innovations in Practical Noise Control (2009).
33.
33. K. J. Rogers and A. Finn, “ Three-dimensional UAV-based atmospheric tomography,” J. Atmos. Ocean. Techn. 30(2), 336344 (2013).
http://dx.doi.org/10.1175/JTECH-D-12-00036.1
34.
34. V. Ostashev, M. V. Scanlon, D. K. Wilson, and S. N. Vecherin, “ Source localization from an elevated acoustic sensor array in a refractive atmosphere,” J. Acoust. Soc. Am. 124(6), 34133420 (2008).
http://dx.doi.org/10.1121/1.3003085
35.
35. A. D. Pierce, Acoustics: An Introduction to its Physical Principles and applications ( McGraw-Hill, New York, 1981), pp. 1619.
36.
36. A. P. Dowling and J. E. Ffowcs Williams, Sound and Sources of Sound ( Horwood, London, 1983), pp. 187208.
37.
37. D. A. Haugen and N. Busch, Workshop on Micrometeorology ( Am. Meteorol. Soc., Boston, 1973).
38.
38. H. A. Panofsky and J. A. Dutton, Atmospheric Turbulence. Models and Methods for Engineering Applications ( Wiley, New York, 1984), pp. 1397.
39.
39. Y. Chenge and W. Brutsaert, “ Flux-profile relationships for wind speed and temperature in the stable atmospheric boundary layer,” J. Bound. Layer Meteorol. 114(3), 519538 (2005).
http://dx.doi.org/10.1007/s10546-004-1425-4
40.
40. M. Optis, A. Monahan, and F. C. Bosveld, “ Moving beyond Monin-Obukhov similarity theory in modelling wind-speed profiles in the lower atmospheric boundary layer under stable stratification,” Bound. Layer Meteorol. 153(3), 497514 (2014).
http://dx.doi.org/10.1007/s10546-014-9953-z
41.
41. J. N. Ash and R. L. Moses, “ Acoustic time delay estimation and sensor network self- localization: Experimental results,” J. Acoust. Soc. Am. 118(2), 841850 (2005).
http://dx.doi.org/10.1121/1.1953307
42.
42. R. Dashen, W. H. Munk, K. M. Watson, and F. Zachariasen, Sound Transmission Through a Fluctuating Ocean ( Cambridge University Press, Cambridge, UK, 1979), pp. 1320.
43.
43. A. J. Weiss and E. Weinstein, “ Fundamental limitations in passive time delay estimation–Part I: Narrow-band systems,” IEEE Trans. Acoust. Speech Sig. Proc. 31(2), 472486 (1983).
http://dx.doi.org/10.1109/TASSP.1983.1164061
44.
44. R. J. Kozick and B. M. Sadler, “ Algorithms for localization and tracking of acoustic sources with widely separated sensors,” in Proceedings of the 2000 Meeting of the IRIS Specialty Group on Battlefield Acoustics and Seismics, Laurel, MD (October 18–20, 2000).
45.
45. K. Rogers and A. Finn, “ 3D acoustic atmospheric tomography,” in Proceedings of the SPIE Conference on Remote Sensing (2014), pp. 92420R92420R-9.
46.
46. B. W. Parkinson and J. J. Spilker, Progress in Astronautics and Aeronautics: Global Positioning System: Theory and Applications ( Am. Inst. Astronaut. Aeronaut., Reston, VA, 1996), pp. 469484.
47.
47. P. D. Schomer, R. Raspet, M. Wagner, D. Walker, and D. Marshall, “ Methods for detecting low-frSSuency signals in the presence of strong winds,” USACERL Technical Report N-90/09, U.S. Army Corps of Engineers Construction Engineering Research Laboratory (1990).
48.
48. M. R. Shust and J. C. Rogers, “ Active removal of wind noise from outdoor microphones using local velocity measurements,” J. Acoust. Soc. Am. 104(3), 17811781 (1998).
http://dx.doi.org/10.1121/1.424141
49.
49. M. R. Stinson, G. A. Daigle, and J. F. Quaroni, “ Airflow noise in telephone handsets and methods for its reduction,” J. Acoust. Soc. Am. 118(1), 205212 (2005).
http://dx.doi.org/10.1121/1.1931087
50.
50. S. Franklin and A. Finn, “ Acoustic sense and avoid (Phase II): Real world validation of performance envelope—final report to the Sir Ross and Sir Keith Research Fund,” Defence and Systems Institute Research Report (2014).
51.
51. A. Finn and S. Franklin, “ Trials results for acoustic sense and avoid for UAVs,” Defence and Systems Institute Report, DA-AS-085-D0070 (2012).
52.
52. K. Rogers and A. Finn, “ 3D UAV-based atmospheric tomography: Preliminary trials results,” in Proceedings of the Australian Acoustical Society Conference, Victor Harbour (2013).
http://aip.metastore.ingenta.com/content/asa/journal/jasa/138/2/10.1121/1.4926900
Loading
/content/asa/journal/jasa/138/2/10.1121/1.4926900
Loading

Data & Media loading...

Loading

Article metrics loading...

/content/asa/journal/jasa/138/2/10.1121/1.4926900
2015-08-17
2016-12-03

Abstract

A technique for remotely monitoring the near-surface air temperature and wind fields up to altitudes of 1 km is presented and examined. The technique proposes the measurement of sound spectra emitted by the engine of a small unmanned aerial vehicle using sensors located on the aircraft and the ground. By relating projected and observed Doppler shifts in frequency and converting them into effective sound speed values, two- and three-dimensional spatially varying atmospheric temperature and wind velocity fields may be reconstructed using tomography. The feasibility and usefulness of the technique relative to existing unmanned aerial vehicle-based meteorological techniques using simulation and trials is examined.

Loading

Full text loading...

/deliver/fulltext/asa/journal/jasa/138/2/1.4926900.html;jsessionid=IdKGVAMDDJ9nXAq0vuT5-qK8.x-aip-live-03?itemId=/content/asa/journal/jasa/138/2/10.1121/1.4926900&mimeType=html&fmt=ahah&containerItemId=content/asa/journal/jasa
true
true

Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
/content/realmedia?fmt=ahah&adPositionList=
&advertTargetUrl=//oascentral.aip.org/RealMedia/ads/&sitePageValue=asadl.org/jasa/138/2/10.1121/1.4926900&pageURL=http://scitation.aip.org/content/asa/journal/jasa/138/2/10.1121/1.4926900'
Right1,Right2,Right3,